Relative importance of regressor variables is an old topic that still awaits a satisfactory solution. When interest is in attributing importance in linear regression, averaging over orderings methods for decomposing R2 are among the state-of-theart methods, although the mechanism behind their behavior is not (yet) completely understood. Random forests—a machinelearning tool for classification a...

Basic chemometric methods for making empirical regression models for QSPR/QSAR are briefly described from a user's point of view. Emphasis is given to PLS regression, simple variable selection and a careful and cautious evaluation of the performance of PLS models by repeated double cross validation (rdCV). A demonstration example is worked out for QSPR models that predict gas chromatographic re...

Supplementary Note 1 DIY Light Sheet Microscope Development Supplementary Note 2 Commercially Available and Construction Protocols for Light Sheet Microscopes Supplementary Note 3 Matching Imaging Technologies to the Sample Supplementary Note 4 Delivery of Illumination to the Sample Supplementary Note 5 Spatial Resolution and Field of View Supplementary Note 6 Objective Lenses for Light Sheet F...

Missing values are endemic in the data sets available to econometricians. This paper suggests a unified likelihood-based approach to deal with several nonignorable missing data problems for discrete choice models. Our concern is when either the dependent variable is unobserved or situations when both dependent variable and covariates are missing for some sampling units. These cases are also con...

Forecasting in the financial domain is undoubtedly a challenging undertaking in data mining. While the majority of previous studies in this field utilize historical market data to predict future stock returns, we explore whether there is benefit in augmenting the prediction model with supplementary domain knowledge obtained from financial news reports. To this end, we empirically evaluate how t...

In this paper, a numerical method is proposed to solve the transient state of Markovian system of equations. Such equations appear in the field of reliability engineering for systems having variable failure and repair rates. Generally, steady state behaviour of the system model is studied due to some constraint on obtaining transient state solution. The proposed method helps to determine the pr...

In this supplementary material, we provide Lemmas 2 and 3 and their proofs. Suppose that x 1 ,. .. , x n are i.i.d. from a probability distribution with mean 0 and finite covariance matrix C = (C jk). Assumption S1: Assume that x 1 has finite fourth moment, that is, E(x 1i x 1 j x 1k x 1l) is finite for any 1 ≤ i, j, k, l ≤ p. Lemma 2 Suppose that Assumption S1 is met. Assumptions 1 and 2 are s...

We recorded neuronal activity in the supplementary eye field (SEF) while monkeys made saccades to targets that yielded rewards of variable amount and uncertainty of delivery. Some SEF cells (29%) represented the anticipated value of the saccade target. These neurons encoded the value of the reward option but did not reflect the action necessary to obtain the reward. A plurality of cells (45%) r...

We present a complete presentation of the theoretical results presented in the main text. We provide detailed analysis of the DStump algorithm in the context of a general additive regression model with uncorrelated design. We derive the results for the linear case as special case of the general theory. Our analysis is high-dimensional and non-asymptotic, and to our knowledge the first such anal...

A new estimation-based Bayesian variable selection approach is presented for genetic analysis of complex traits based on linear or logistic regression. By assigning a mixture of uniform priors (MU) to genetic effects, the approach provides an intuitive way of specifying hyperparameters controlling the selection of multiple influential loci. It aims at avoiding the difficulty of interpreting ass...