"Euclidean distance geometry is the study of Euclidean geometry based on the concept of distance. This is useful in several applications where the input data consists of an incomplete set of distances, and the output is a set of points in Euclidean space that realizes the given distances. We survey some of the theory of Euclidean distance geometry and some of the most important applications: molecular conformation, localization of sensor networks and statics."

"A system responding to a stochastic driving signal can be interpreted as computing, by means of its dynamics, an (implicit) model of the environmental variables. The system's state retains information about past environmental fluctuations, and a fraction of this information is predictive of future ones. The remaining nonpredictive information reflects model complexity that does not improve predictive power, and represents the ineffectiveness of the model. We expose the fundamental equivalence between this model inefficiency and thermodynamic inefficiency, measured by the energy dissipated during the interaction between system and environment. Our results hold arbitrarily far from thermodynamic equilibrium and are applicable to a wide range of systems, including biomolecular machines. They highlight a profound connection between the effective use of information and efficient thermodynamic operation: any system constructed to keep memory about its environment and to operate energetically efficiently has to be predictive."

"A characteristic feature of functional data is the presence of time variability in addition to amplitude variability. The existing functional regression methods do not handle time variability in an explicit and efficient way. In this paper we introduce a functional regression method that incorporates time warping as an intrinsic part of the model. The method achieves good predictive power in a parsimonious way, and allows for unified statistical inference of time and amplitude variability. The properties of the estimators are studied by simulation, and an application to the modeling of ground-level ozone trajectories is presented."

"A new model for computer simulation of solids, composed of bonded particles, is proposed. Vectors rigidly connected with particles are used for description of deformation of a single bond. The expression for potential energy of the bond and corresponding expressions for forces and moments are proposed. Formulas, connecting parameters of the model with longitudinal, shear, bending and torsional stiffnesses of the bond, are derived. It is shown that the model allows to describe any values of the bond stiffnesses exactly. Two different calibration procedures depending on bond length/thickness ratio are proposed. It is shown that parameters of model can be chosen so that under small deformations the bond is equivalent to either Bernoulli-Euler or Timoshenko rod or short cylinder connecting particles. Simple expressions, connecting parameters of V-model with geometrical and mechanical characteristics of the bond, are derived. Computer simulation of dynamical buckling of the straight discrete rod and discrete half-spherical shell is carried out."

Nested sampling is a Bayesian sampling technique developed to explore probability distributions lo- calised in an exponentially small area of the parameter space. The algorithm provides both posterior samples and an estimate of the evidence (marginal likelihood) of the model. The nested sampling algo- rithm also provides an efficient way to calculate free energies and the expectation value of thermodynamic observables at any temperature, through a simple post-processing of the output. Previous applications of the algorithm have yielded large efficiency gains over other sampling techniques, including parallel tempering (replica exchange). In this paper we describe a parallel implementation of the nested sampling algorithm and its application to the problem of protein folding in a Go-type force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations. We demonstrate the method by conducting folding simulations on a number of small proteins which are commonly used for testing protein folding procedures: protein G, the SH3 domain of Src tyrosine kinase and chymotrypsin inhibitor 2. A topological analysis of the posterior samples is performed to produce energy landscape charts, which give a high level description of the potential energy surface for the protein folding simulations. These charts provide qualitative insights into both the folding process and the nature of the model and force field used.

Motivation: NMR spectra are widely used in metabolomics to obtain metabolite profiles in complex biological mixtures. Common methods used to assign and estimate concentrations of metabolite involve either an expert manual peak fitting or extra pre-processing steps, such as peak alignment and binning. Peak fitting is very time consuming and is subject to human error. Conversely, alignment and binning can introduce artifacts and limit immediate biological interpretation of models. Results: We present the Bayesian AuTomated Metabolite Analyser for NMR spectra (BATMAN), an R package which deconvolves peaks from 1-dimensional NMR spectra, automatically assigns them to specific metabolites and obtains concentration estimates. The Bayesian model incorporates information on characteristic peak patterns of metabolites and is able to account for shifts in the position of peaks commonly seen in NMR spectra of biological samples. It applies a Markov Chain Monte Carlo (MCMC) algorithm to sample from a joint posterior distribution of the model parameters and obtains concentration estimates with reduced mean estimation error compared with conventional numerical integration methods.

To model printing noise a binary noisy channel and a set of controlled gates are introduced. The channel input is an image created by a halftoning algorithm and its output is the printed picture. Using this channel robustness to noise between halftoning algorithms can be studied. We introduced relative entropy to describe immunity of the algorithm to noise and tested several halftoning algorithms.

"As in the car industry for quite some time, dynamic simulation of complete vehicles is being practiced more and more in the development of off-road machinery. However, specific questions arise due not only to company structure and size, but especially to the type of product. Tightly coupled, non-linear subsystems of different domains make prediction and optimisation of the complete system's dynamic behaviour a challenge. Furthermore, the demand for versatile machines leads to sometimes contradictory target requirements and can turn the design process into a hunt for the least painful compromise. This can be avoided by profound system knowledge, assisted by simulation-driven product development. This paper gives an overview of joint research into this issue by Volvo Wheel Loaders and Linkoping University on that matter, lists the results of a related literature review and introduces the term "operateability". Rather than giving detailed answers, the problem space for ongoing and future research is examined and possible solutions are sketched."

"The stochastic dynamics of an active particle undergoing a constant speed and additionally driven by an overall fluctuating torque is investigated.…"

"We show that parametric context-sensitive L-systems with affine geometry interpretation provide a succinct description of some of the most fundamental algorithms of geometric modeling of curves. Examples include the Lane-Riesenfeld algorithm for generating B-splines, the de Casteljau algorithm for generating Bezier curves, and their extensions to rational curves. Our results generalize the previously reported geometric-modeling applications of L-systems, which were limited to subdivision curves."

"On a more philosophical level, our approach points at novel questions that go beyond supervised and semi-supervised learning. What benefit do labels provide over unsupervised training? Can our framework be extended to semi-supervised learning where a few labels do exist? Can it be extended to non-classification scenarios such as margin based regression or margin based structured prediction? When are the assumptions likely to hold and how can we make our framework even more resistant to deviations from them? These questions and others form new and exciting open research directions."

"High-dimensional correlated data pose challenges in model selection and predictive learning. In this paper, we derive an iterative thresholding technique for generalized linear models (GLMs) with possibly nonorthogonal designs. We propose a family of $\Theta$-estimators which are associated with penalized likelihoods and can be computed by thresholding-based iterative procedures. It can also be used to robustify GLMs and extend the canonical $M$-estimators.…"

"Systems whose organization displays causal asymmetry constraints, from evolutionary trees to river basins or transport networks, can be often described in terms of directed paths (causal flows) on a discrete state space. Such a set of paths defines a feed-forward, acyclic network. A key problem associated with these systems involves characterizing their intrinsic degree of path reversibility: given an end node in the graph, what is the uncertainty of recovering the process backwards until the origin? Here we propose a novel concept, \textit{topological reversibility}, which rigorously weigths such uncertainty in path dependency quantified as the minimum amount of information required to successfully revert a causal path.…"

"We propose a degree-based coarse graining approach that not just accelerates the evaluation of dynamics on complex networks, but also satisfies the consistency conditions for both equilibrium statistical distributions and nonequilibrium dynamical flows. For the Ising model and susceptible-infected-susceptible epidemic model, we introduce these required conditions explicitly and further prove that they are satisfied by our coarse-grained network construction within the annealed network approximation. Finally, we numerically show that the phase transitions and fluctuations on the coarse-grained network are all in good agreements with those on the original one."

"In this paper, we investigate a conjecture by von Haeseler concerning the Maximum Parsimony method for phylogenetic estimation, which was published by the Newton Institute in Cambridge on a list of open phylogenetic problems in 2007. This conjecture deals with the question whether Maximum Parsimony trees are hereditary. The conjecture suggests that a Maximum Parsimony tree for a particular (DNA) alignment necessarily has subtrees of all possible sizes which are most parsimonious for the corresponding subalignments. We answer the conjecture affirmatively for binary alignments on five taxa but also show how to construct examples for which Maximum Parsimony trees are not hereditary. …we also show that compatible most parsimonious quartets do not have to provide a most parsimonious supertree. Last, we show that our results can be generalized to Maximum Likelihood for certain nucleotide substitution models."

"We study several problems related to finding reset words in deterministic finite automata. In particular, we establish that the problem of deciding whether a shortest reset word has length k is complete for the complexity class DP. This result answers a question posed by Volkov. For the search problems of finding a shortest reset word and the length of a shortest reset word, we establish membership in the complexity classes FP^NP and FP^NP[log], respectively. Moreover, we show that both these problems are hard for FP^NP[log]. Finally, we observe that computing a reset word of a given length is FNP-complete."

"Since the collective beliefs are not given to modifica- tions within short timescales, the best approach for one opinion to win is to focus on getting as many as pos- sible inflexibles along its side. However this goal could demand to overstate the validity of some arguments to sustain and legitimate that opinion. In contrast, such a behavior could rise ethical questions.…"

"…We find that a well-defined temporal component exists and accounts for some of the variance in the data. This temporal component arises because active regions with high magnetic field strength evolve, breaking up into small-scale magnetic elements with low field strength, and radiative and magnetic fluxes are sensitive to different active-region components. We generate empirical models that relate radiative flux to magnetic flux, allowing us to predict spectral-irradiance variations from observations of disk-averaged magnetic-flux density. In most cases, the model reconstructions can account for 85-90% of the variability of the radiative flux from the chromosphere and corona. Our results are important for understanding the relationship between magnetic and radiative measures of solar and stellar variability."

"A widely used tool in the study of risk, insurance and extreme values is the mean excess plot. One use is for validating a generalized Pareto model for the excess distribution. This paper investigates some theoretical and practical aspects of the use of the mean excess plot."

"Monte Carlo methods play an important role in scientific computation, especially when problems have a vast phase space. In this chapter an introduction to the Monte Carlo method is given. Concepts such as Markov chains, detailed balance, critical slowing down, and ergodicity, as well as the Metropolis algorithm are explained. The Monte Carlo method is illustrated by numerically studying the critical behavior of the two-dimensional Ising ferromagnet using finite-size scaling methods. Furthermore, advanced Monte Carlo methods are described (parallel tempering Monte Carlo) and illustrated with nontrivial models from the physics of glassy systems."

"We present a method for the reconstruction of networks, based on the order of nodes visited by a stochastic branching process. Our algorithm reconstructs a network of minimal size that ensures consistency with the data. Crucially, we show that global consistency with the data can be achieved through purely local considerations, inferring the neighbourhood of each node in turn. The optimisation problem solved for each individual node can be reduced to a Set Covering Problem, which is known to be NP-hard but can be approximated well in practice. We then extend our approach to account for noisy data, based on the Minimum Description Length principle. We demonstrate our algorithms on synthetic data, generated by an SIR-like epidemiological model."

"For instance, there is the Rogue Factory unit producing "custom high-tech goods"—but "what would the black market of 'special orders' look like?" Benque asks. This "black market of 'special orders'" for things like 3D-printed human organs would also be something quite extraordinary to see, given another two decades' time and cheap-enough bio-ink."

"This paper introduces the FLOSS Free Libre Open Source Software [VEMSA3D], a contraction of "Visual Electromagnetic Simulator for 3D Antennas", which are geometrically modeled, either exactly or approximately, as thin wire polygonal structures; presents its GUI Graphical User Interface capabilities, in interactive mode and/or in handling suitable formed antenna data files; demonstrates the effectiveness of its use in a number of practical antenna applications, with direct comparison to experimental measurements and other freeware results; and provides the inexperienced user with a specific list of instructions to successfully build the given source code by using only freely available IDE Integrated Development Environment tools-including a cross-platform one.…"

"Random numbers play a crucial role in science and industry. Many numerical methods require the use of random numbers, in particular the Monte Carlo method. Therefore it is of paramount importance to have efficient random number generators. The differences, advantages and disadvantages of true and pseudo random number generators are discussed with an emphasis on the intrinsic details of modern and fast pseudo random number generators. Furthermore, standard tests to verify the quality of the random numbers produced by a given generator are outlined. Finally, standard scientific libraries with built-in generators are presented, as well as different approaches to generate nonuniform random numbers. Potential problems that one might encounter when using large parallel machines are discussed."

"Adaptive networks have been recently introduced in the context of disease propagation on complex networks. They account for the mutual interaction between the network topology and the states of the nodes. Until now, existing models have been analyzed using low-complexity analytic formalisms, revealing nevertheless some novel dynamical features. However, current methods have failed to reproduce with accuracy the simultaneous time evolution of the disease and the underlying network topology. In the framework of the adaptive SIS model of Gross et al. [Gross et al., Phys. Rev. Lett. 96, 208701 (2006)], we introduce an improved compartmental formalism able to handle this coevolutionary task successfully. With this approach, we analyze the interplay and outcomes of both dynamical elements, process and structure, on adaptive networks featuring different degree distributions at the initial stage."

"…Since the produced mesh is applied to the meshless-type methods, the connectivity of the points is not used and only the grid points are important, though the grid lines are utilized in the adapting process. The performance of the adaptive points is exam- ined by considering a collocation meshless method which is based on interpolation in terms of a set of radial basis functions. … Some experimental results will be presented to illustrate the effectiveness of the proposed method."

"In the present work we introduce a novel multi-agent model with the aim to reproduce the dynamics of a double auction market at microscopic time scale through a faithful simulation of the matching mechanics in the limit order book. The model follows a "zero intelligence" approach where the actions of the traders are related to a stochastic variable, the market sentiment, which we define as a mixture of public and private information. The model, despite the parsimonious approach, is able to reproduce several empirical features of the high-frequency dynamics of the market microstructure not only related to the price movements but also to the deposition of the orders in the book."

"…For example, when estimating a contour integral of an analytic function, we might transform the contour to a circle and use equally spaced points on the circle.

However, when simulating Canberra’s future climate and water supply, it would not be a good idea to assume that exceptionally dry years were equally spaced!…"

"The properties of polymer liquids on hard and soft substrates are investigated by molecular dynamics simulation of a coarse-grained bead-spring model and dynamic single-chain-in-mean-field (SCMF) simulations of a soft, coarse-grained polymer model. Hard, corrugated substrates are modelled by an FCC Lennard-Jones solid while polymer brushes are investigated as a prototypical example of a soft, deformable surface. From the molecular simulation we extract the coarse-grained parameters that characterise the equilibrium and flow properties of the liquid in contact with the substrate: the surface and interface tensions, and the parameters of the hydrodynamic boundary condition. The so-determined parameters enter a continuum description like the Stokes equation or the lubrication approximation."

"A simple test is proposed for examining the correctness of a given completely specified response function against unspecified general alternatives in the context of univariate regression. The usual diagnostic tools based on residuals plots are useful but heuristic. We introduce a formal statistical test supplementing the graphical analysis. Technically, the test statistic is the maximum length of the sequences of ordered (with respect to the covariate) observations that are consecutively overestimated or underestimated by the candidate regression function. Note that the testing procedure can cope with heteroscedastic errors and no replicates. Recursive formulae allowing to calculate the exact distribution of the test statistic under the null hypothesis and under a class of alternative hypotheses are given."

"This article describes the R package DEoptim which implements the differential evolution algorithm for the global optimization of a real-valued function of a real-valued parameter vector. The implementation of differential evolution in DEoptim interfaces with C code for efficiency. The utility of the package is illustrated via case studies in fitting a Parratt model for X-ray reflectometry data and a Markov-Switching Generalized AutoRegressive Conditional Heteroskedasticity (MSGARCH) model for the returns of the Swiss Market Index."

"The goals of this challenge are to (1) learn the relative strengths and weaknesses of the different classification algorithms, (2) use the results to improve classification algorithms, and (3) understand what spectroscopically confirmed sub-sets are needed to properly train these algorithms. The challenge is available at www.hep.anl.gov/SNchallenge, and the due date for classifications is May 1, 2010."

via: Genetic Argonaut

"Which neatly illustrates one major reason why, at the end of the day, I write this blog. Sitting down to keyboard with cigar and libation in hand does wonders to clarify not only my own thoughts on any particular subject, but also whether it rises to the level of something I might find interesting from another pen. If not, back to the woodpile it goes, where I can scavenge it for useful material later or consign it to the fireplace for fuel. The false starts, dead ends, and inchoate beginnings embodied in my unpublished oeuvre represent the very essence of active thought. Too bad I'll never let you see them in all their messy glory. If you did, you just might begin to believe that I don't really know what I'm talking about.<2>

Now, if you'll excuse me, I must get back to chasing those tops. I'll get back to you if I catch one that's interesting."

"The place where I think Sloman is misguided is in his formulation of scientific models in an either/or way, as if, in truth, social variables are linked in simple causal paths, with a scientific goal of figuring out if A causes B or the reverse. I don't know much about intelligence, beer consumption, and socioeconomic status, but I certainly don't see any simple relationships between income, religious attendance, party identification, and voting--and I don't see how a search for such a pattern will advance our understanding, at least given current techniques. I'd rather start with description and then go toward causality following the approach of economists and statisticians by thinking about potential interventions one at a time. I'd love to see Sloman's and Pearl's ideas of the interplay between observational and experimental data developed in a framework that is less strongly tied to the notion of choice among simple causal structures."

"It was also realised that had the layout optimization solver been incorporated within a user-friendly interactive software package, then it would have been very much easier to rapidly change the design problem in response to feedback from other members of the design team..."

Want to breed replacements for the models in Section 4

"Perhaps by coincidence, three new papers in this week’s issue of the NEP-DGE report deal with forecasting. Kolasa, Rubaszek and Skrzypczyński says that DSGE models perform remarkably well. Bache, Jore, Mitchell and Vahey claim that VAR models with structural breaks do better, but of course structural breaks cannot be predicted with a VAR. Gupta, Kabundi and Miller show that DSGE models of real estate markets are better with turning points, which are the most difficult statistic to forecast."

"There are important uses for financial products, even complicated ones, so I don't want to impugn innovation generally, but I also don't want to adopt the position that it was all useful - it clearly wasn't and stronger regulatory oversight is needed. As for the defense of financial models and innovation described above, the statement that innovation generally is the source of economic growth, therefore financial innovation must also be good, isn't much help. Similarly, if saying "models benefit many fields, such as airline safety, and not only financial markets" is the best defense of risk models available, that's telling."

"Faro Measuring System's Laser ScanArm might bring back bad memories of the dentist, but in fact it's another 3D scanning solution--this one mounted to an articulated arm that not only helps you hold it steady, but records the scanner's position in space. Faro's Orlando Perez shoots and captures a mini Lady Liberty:..."

"Today’s class in ENG 198, Introduction to the Missing Basics of Engineering (syllabus here), is covering engineering modeling in the lecture Engineering and Models: Hint – Real Engineers Use More than Just Equations."

"WOB combines a database of bifurcation problems with a tutorial on nonlinear phenomena.

WOB is designed to be part of a virtual university. The approach is example-oriented and experimental. The emphasis is on examples that are application-oriented."

"The puzzle: The puzzle is to find the flaw, the erroneous step, in the switching argument above. This includes determining exactly why and under what conditions that step is not correct, in order to be sure not to make this mistake in a more complicated situation where the misstep may not be so obvious. In short, the problem is to solve the paradox."

See in particular Chapter 2, on Data Balancing. This is important stuff for those of us dealing with data-driven models and techniques, especially those not based on analytical closed form first-principles junk.

"Let's go through a specific example of setting up a Semantic Forms-based wiki from scratch. Let's say that you want to create a wiki that shows all the books you have at home. We'll then go through the steps specified in "Getting started"."

"But what if the underlying basis for the model is wrong? That is the message of Merritts and Walters’ Science article. It “was like a bomb, in a good way,” says Frank Pazzaglia, a geology professor at Lehigh University in Bethlehem, Pa. Earlier generations of geomorphologists had recognized the widespread nature of legacy sediments but had attributed them solely to high post-settlement erosion, he says. “More recent workers had focused on the processes, such as how does sediment move, and less on the history. Now we have both pieces. Furthermore, by adding the hard data on milldams, Merritts and Walter have made this legacy better understood.”"

"1) Rational solutions need not be universal, instead they will be only effective in appropriate contexts.

2) Rationally acceptable conclusions do not have to follow necessarily from the information given, as acceptance is not to be understood in terms of a formal relationship between propositions but in terms of a practical commitment.

3) The rationality of the conclusions is not necessarily determined by whether they conform to the appropriate rules, indeed the primary focus is removed from conclusions and placed upon actions that are taken on the basis of beliefs and methods that are all subject to further criticism and development. "

"Most mainstream macroeconomic theoretical innovations since the 1970s (the New Classical rational expectations revolution associated with such names as Robert E. Lucas Jr., Edward Prescott, Thomas Sargent, Robert Barro etc, and the New Keynesian theorizing of Michael Woodford and many others) have turned out to be self-referential, inward-looking distractions at best. Research tended to be motivated by the internal logic, intellectual sunk capital and esthetic puzzles of established research programmes rather than by a powerful desire to understand how the economy works - let alone how the economy works during times of stress and financial instability. So the economics profession was caught unprepared when the crisis struck."

"Foolish reliance on Li's model lead to disaster and it was made possible by CDS markets which convinced participants that they had many observations on the probability of default. They were convinced that prices revealed these probabilities because they had an insane mystical faith in the strong form efficient markets hypothesis and a schizophrenic simultaneous belief that they could beat the market."

"I am mainly interested in how scientific method could possibly lead us to true generalizations about Nature; generalizations that extend infinitely beyond our current, finite perspective. Standard philosophy of science sidesteps this question by asking, instead, about the meanings of "justification" and "rationality" a different matter entirely. I put the former question front and center, so that methodological normativity must be traced back to truth-finding efficacy, rather than to sociological generalizations about scientific practice. In this respect, my approach to epistemology closely parallels work in theoretical computer science and the foundations of mathematics, in which the central question is existence of a reliable procedure for finding the right answer to a question. The shift in emphasis results in a fresh, new perspective on a number of standard issues in epistemology and the philosophy of science, such as:..."

"The damage was foreseeable and, in fact, foreseen. In 1998, before Li had even invented his copula function, Paul Wilmott wrote that "the correlations between financial quantities are notoriously unstable." Wilmott, a quantitative-finance consultant and lecturer, argued that no theory should be built on such unpredictable parameters. And he wasn't alone. During the boom years, everybody could reel off reasons why the Gaussian copula function wasn't perfect. Li's approach made no allowance for unpredictability: It assumed that correlation was a constant rather than something mercurial. Investment banks would regularly phone Stanford's Duffie and ask him to come in and talk to them about exactly what Li's copula was. Every time, he would warn them that it was not suitable for use in risk management or valuation..."

"Yet Clojure offers many advantages over its dialectical ancestors. The first is immutable data structures. This forces you to think about everything as input and output (good for modeling) while making it easier to think and reason about (good for understanding your model) your program. The differentiation that Clojure makes between identity and state is also a good fit for modeling. Clojure is also built for a concurrent world. Clojure can handle a lot of different parts of a program simultaneously reading and writing changes to the world, allowing you to focus on each part of your system as individuals rather than worrying about the mechanics of making them all work together. Clojure also keeps vectors and hash tables as built-in, both convenient data structures for modeling tasks."

In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6.
"What are you doing?", asked Minsky.
"I am training a randomly wired neural net to play Tic-Tac-Toe," Sussman replied.
"Why is the net wired randomly?", asked Minsky.
"I do not want it to have any preconceptions of how to play", Sussman said.
Minsky shut his eyes.
"Why do you close your eyes?", Sussman asked his teacher.
"So that the room will be empty."
At that moment, Sussman was enlightened.

Trying to learn a bit more about this, to reconcile it with my understanding of agile design. Thinking there may be an incremental path between agile development and formal completeness/consistency... but it would be a path of practice meeting a path of logical modeling, and that will be complex and interesting and difficult to elucidate.

"In a scientific context what does this mean? The overall project referred to is your analysis. The activities are simple operations within your analysis. All these operations have a certain number of inputs and outputs. In the case of fetching a DNA sequence, an input may be an identifier of the sequence, whilst the output is a string representing the nucleotide sequence represented by this identifier.
The triggering of activities by other activities are where an operation feeds data into a subsequent operation. For example, the ‘fetch sequence’ operation may feed its output (the string containing sequence ‘ACTG’) into a ‘transcribe’ operation. This would subsequently change the DNA sequence into an RNA sequence. We would then have a simple workflow with one operation, and a link, which looks something like the following:..."

"Pyflix is a small package written in Python that provides an easy entry point for getting up and running in the Netflix Prize competition. It combines an efficient storage scheme with an intuitive high-level API that allows contestants to focus on the real problem, the recommendation system algorithm. To get started with Pyflix, keep reading."

reproduce this using Pareto-GP?

"Timer Seeds is a small group of timing-industry professionals (either strategy developers like me or sales/marketing) with an idea that goes something like this:

No matter how good we are at developing strategies and managing money, there are unsung developers out there, laboring away in their basements, that are even better. But because they lack either the ability or the time, their strategies never ever leave that basement. They never make the transition to becoming a professional strategy developer.

And based on that vision, we launched Timer Seeds. We find developers, take the required steps to make their programs marketable, and then place their programs with investors, financial advisors, hedge funds, and other industry professionals. The developer receives a percentage of assets under management, something that can become very lucrative for very good programs."

"Flight to quality? Some real hedge funds are positive for the year even when the aggregate returns for the industry are negative. Performance dispersion is enormous in such a diverse universe. Several strategies have not been affected by prime brokers imploding, changes in short selling rules or the leverage lockdown. The best managed futures CTAs, global macro and options traders have been generating absolute returns throughout the equity and credit mayhem. Strategy diversification is so important since forecasting is difficult. Transitions from one market regime to another often requires a financial revolution."

“Post-autistic economics” (PAE) is the name now taken by those few economists who hope to rescue the discipline from the neoclassical model; the name is an homage to the dissident French students, whose manifesto called the standard model “autistic.” It is a hilariously apt (albeit mildly offensive) diagnosis, and it could be just as well applied to Homo economicus himself, the economic actor envisioned by the neoclassical theory, who performs dazzling calculations of utility maximization despite being entirely unable to communicate with his fellow man.

"... Unlike most pollsters, Penn never releases his raw numbers, only his analysis. So we must take it on faith that his methodology is rigorous, his polls accurate and his interpretations fair. This book is our first opportunity to observe, at length, how adroitly Penn handles raw data. And the answer is stunning, even to a doubter like me. Mark Penn cannot handle numbers. If this book were turned in as the final to an entry-level statistics class, Penn would not only be failed, but the professor might well retire in shame."

Seems like a useful starting point for a genetic programming excursion....

"I have for all my mature life been impressed by people's tenacity, and in no specific more than discussion, whether in electronic forums or newspapers' letters to the editor..."