# Jump Diffusion processes via EM-Algorithm

The following source code and source code examples are about Jump Diffusion processes that Calculates parameters for Jump Diffusion processes via EM-Algorithm.

The following source code and source code examples are about Empirical-likelihood test that calculates the p-value for a mean-type hypothesis based on two samples.

The following source code and source code examples are about Risk prediction Analysis that is an adaptive index classification algorithm which selects features based on differential variability and is aimed at DNA methylation array studies.

The following source code and source code examples are Misc function for working with eyetracking data.

The following source code and source code examples are about Factor Mixture Analysis with covariates .The package estimates Factor Mixture Analysis via the EM algorithm.

The following source code and source code examples are about Scores features for Feature seLection.For each feature, a score is computed that can be useful for feature selection.

The following source code and source code examples are about Generalized Archimedean Copula. Bi-variate data fitting is done by two stochastic components: the marginal distributions and the dependency structure.

The following source code and examples are used for image segmentation using EM-like algorithms that is based on A convergence theorem for Variational EM-like algorithms : application to image segmentation.

The following source code and examples are used for inference in logistic regression models.

The following source code and examples are used for Statistical Methods in Forensic Genetics. That can generate statistical evaluation of DNA mixtures, DNA profile match probability.

The following source code and examples are used for Forward search approach to robust analysis in linear and generalized linear regression models.

The following source code and examples are used for Frequency Moving Average Plots. A frequency moving average plot (MAP) is estimated from a multinomial data and a continuous covariate.

The following source code and examples are used for Full Randomization Test.

The following source code and examples are used for Analyzing Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Data.

The following source code and examples are integrative tool for analyzing gene co-expression networks built from microarray expression data.

The following source code and examples are about Genetic Algorithm for the determination of the stratum boundaries and sample sizes of each stratum in stratified samplingused to analyse complex ANOVA models.

The following source code and examples are used to analyse complex ANOVA models.

The following source code and examples are a collection of utilities for analyzing censored and uncensored data from generalized Birnbaum-Saunders distributions.

The following source code and examples are used for genetic algorithm for binary and floating point chromosomes.

The following source code and examples are used for implementing several generalized F-statistics.

The following source code and examples are used for inferring time delay gene regulatory network using time course gene expression profiles.

This package provides two generic functions for performing Markov chain sampling in a naive way for a user-defined target distribution, which involves only continuous variables.

The following source code and examples are used to implement a permutation-based testing procedure to globally test the (additional) predictive value of a large set of predictors.

This package computes the bootstrap goodness-of-fit test for the generalized Pareto distribution by Villasenor-Alva and Gonzalez-Estrada

The following source code and examples are used for Global Validation of Linear Models Assumptions.

The following source code and examples are used for estimating covariate relative risks in case-control data by weighted logistic regression.

The following package and source code is based on 2008: A. M. Atto and D. Pastor and G. Mercier, Detection Threshold for Non-Parametric Estimation, Signal, Image and Video Processing, Springer, Vol. 2, No. 3.

The following package and source code is based on 2009: A. M. Atto and D. Pastor and G. Mercier, Smooth Adaptation by Sigmoid Shrinkage, EURASIP Journal on Image and Video Processing, Elsevier.

The following package and source code is based on 2010: A. M. Atto and D. Pastor, Central Limit Theorems for Wavelet Packet Decompositions of Stationary Random Processes, IEEE Transactions on Signal Processing, Vol. 58, No. 2.

The following package and source code is based on 2010: A. M. Atto and D. Pastor and G. Mercier, Wavelet Packets of fractional Brownian motion: Asymptotic Analysis and Spectrum Estimation , IEEE Transactions on Information Theory, Vol. 56.