- Referenced in 9969 articles
- variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering...
- Referenced in 552 articles
- graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. Please...
- Referenced in 407 articles
- package ismev: An Introduction to Statistical Modeling of Extreme Values. Functions to support the computations ... carried out in ‘An Introduction to Statistical Modeling of Extreme Values’ by Stuart Coles ... divided into the following groups; maxima/minima, order statistics, peaks over thresholds and point processes...
- Referenced in 440 articles
- with, and searches for causal and statistical models. The aim of the program ... friendly interface requiring very little statistical sophistication of the user and no programming knowledge ... intended to replace flexible statistical programming systems such as Matlab, Splus or R. Tetrad ... confounders of measured variables, to search for models of latent structure, and to search...
- Referenced in 378 articles
- Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. The project...
- Referenced in 344 articles
- statistical methods and material on statistical modelling in R. The book is written ... even in the case of advanced statistical notions. The book is intended as a text...
- Referenced in 346 articles
- Mplus is a statistical modeling program that provides researchers with a flexible tool to analyze...
- Referenced in 253 articles
- Fahrmeir: Data from the book ”Multivariate Statistical Modelling Based on Generalized Linear Models”, first edition ... functions for the book ”Multivariate Statistical Modelling Based on Generalized Linear Models”, version...
- Referenced in 673 articles
- Collection), data mining (IBM SPSS Modeler), text analytics, statistical analysis, and collaboration and deployment (batch...
- Referenced in 408 articles
- states to represent the error statistics of the model estimate, it applies ensemble integrations ... predict the error statistics forward in time, and it uses an analysis scheme which operates ... directly on the ensemble of model states when observations are assimilated. The EnKF has proven...
- Referenced in 308 articles
- fields. Theory and applications. Researchers in spatial statistics and image analysis are familiar with Gaussian ... data, spatio-temporal models, graphical models, and semi-parametric statistics. With so many applications ... widespread use in the field of spatial statistics, it is surprising that there remains ... GMRFs in complex hierarchical models, in which statistical inference is only possible using Markov Chain...
- Referenced in 491 articles
- package robustbase: Basic Robust Statistics. ”Essential” Robust Statistics. The goal is to provide tools allowing ... This includes regression methodology including model selections and multivariate statistics where we strive to cover...
- Referenced in 758 articles
- special case of the linear mixed model or its generalized counterpart. This book is very ... statistically oriented scientists who have a good working knowledge of linear models and the desire...
- Referenced in 725 articles
- financial modeling, theoretical and quantum chemistry, chemical process simulation, mathematics and statistics, power networks...
- Referenced in 119 articles
- Ronald Gallant’s, ”Nonlinear Statistical Models”. The program computes least squares estimates for a univariate...
- Referenced in 117 articles
- also used as the basis for statistical model representations, such as linear and nonlinear regression...
- Referenced in 236 articles
- framework encompassing machine learning, graphical models, and Bayesian statistics (hence the logo). (Some methods from...
- Referenced in 764 articles
- statistics courses on subjects like multivariate analysis, time series analysis and generalized linear modelling...
- Referenced in 97 articles
- data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more...
- Referenced in 83 articles
- develop a Bayesian “sum-of-trees” model where each tree is constrained by a regularization ... particular, BART is defined by a statistical model: a prior and a likelihood. This approach...