# Selection Response Analysis

The following R package and source code is used to analyse artificial-selection response datasets.The parameters underlying the dynamics of the time series are estimated by maximum likelihood.

The following R package and source code is used to calculate appropriate sample sizes for one-sample t-tests, two-sample t-tests, and F-tests.

The following R package and source code is used for estimation of the parameters of a spatio-temporal model using the EM algorithm.

The following R package and source code is about method to explore the treatment-covariate interactions in survival data arising from two treatment arms of a clinical trial.

The following R package and source code is about interpolation based on piecewise rational functions using Stineman's algorithm.

The following R package and source code is used for Solving stochastic linear programs with a single risk constraint.

The following R package and source code is used for analyzing paleontological and geological data distributed through through time in stratigraphic cores or sections.

The following R package and source code is used for computing the reliability of stress-strength models and for building two-sided or one-sided confidence intervals.

The following R package and source code implements various symbol plots, such as bars, profiles, stars, Chernoff faces, color icons, stick figures.

The following R package and source code is used for Time Course Analysis of Variance time course microarray data.

The following R package and source code is used for Sampling designs and parameter estimation in finite population.

The following R package and source code is used for Statistical interpretation of forensic glass transfer.

The following R package and source code is used for Tilted Correlation Screening algorithm in high-dimensional linear regression.

The following R package and source code is used for Titration analysis for mass spectrometry data.

The following R package and source code is used for General discrete triangular distribution.

The following R package and source code is used for Trimmed k-means clustering.

The following R package and source code performs Least angle regression for time series analysis.

The following R package and source code performs survival and quantitative outcome using time-course gene expression.

The following R package and source code is used for conducting large-scale inference on the rows of a data matrix.

The following R package and source code is used Function estimation via Unbalanced Haar wavelets. Top-down and bottom-up algorithms are used for nonparametric function estimation in Gaussian noise.

The following R package and source code is used for External and Internal Validation Indices.

The following R package and R code is about violin plot with mean and standard deviation.

The following R package and R code is about Wavelet change point detection for array CGH data.

The following R package and R code is about wavelet routines that calculate single sets of wavelet multiple correlations and cross-correlations out of n variables.

The following R package and R code Provides classes, methods, and examples for use in wildlife research and management.

The following R package and R code Analyses individually geo-referenced multilocus genotypes for the inferences of genetic boundaries between populations.

The following matlab code and examples is about MatLab code for the quadratic Koch curve.

Inversion to obtain a PM space from a stress-strain curve. (Uses a Monte Carlo (random shift method)) Ability to start with a custom PM distribution for inversion Limited to inverting up-down stress protocols (no inner loops) Forward problem works for all stress protocols Faster testing and prediction of stress protocols Ability to add new PM distributions Ability to save and load PM spaces,

It interfaces with a webcam attached to the computer, uses it to capture an image of a bacterial plate and counts the number of colonies on the dish.

The following matlab code and examples is about Adaptive Mixture Modelling Metropolis Methods for Bayesian Analysis of Non-linear State-Space Models.