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Mi band tools xdating


Sat, 31 Oct CRANberries is back Apologies for the service interruption but Comcast had decided to throw me a particularly nasty curveball. A more detailed post may appear on my blog in a bit. In the meantime, enjoy the pent-up listing of fifty-five new entries and sorry about the service interruption. Fri, 30 Oct Package phangorn updated to version 0. Phylogenetic analysis in R Description: Mi band tools xdating coin updated to version 1.

Conditional inference procedures for the general independence problem including two-sample, K-sample non-parametric ANOVAcorrelation, censored, ordered and multivariate problems.

Diff between coin versions 1. New package Guerry with initial version 1. Michael Friendly and Stephane Dray Maintainer: This package comprises maps of France indata from A. Guerry and others and statistical and graphic methods related to Guerry's "Moral Statistics of France". New package zic with initial version 0. This package provides MCMC algorithms for the analysis of zero-inflated count models. The case of stochastic search variable selection SSVS is also considered.

A data set considering the demand for health care is also provided. Package svUnit updated to version 0. Package rsm updated to version 1. Provides functions to generate response-surface designs, fit first- and second-order response-surface models, make contour plots, obtain the path of steepest ascent, and do canonical analysis.

Diff between rsm versions 1. Package meta updated to Mi band tools xdating 1.

Meta-Analysis with R Description: Fixed and random effects meta-analysis. Functions for tests of bias, forest and funnel plot. Diff between meta versions 1. R meta Rd 52 meta Package accuracy updated to version 1.

Tools for testing and improving accuracy of statistical results. This is a suite of tools designed to test and improve the accuracy of statistical computation, including: Diff between accuracy versions 1.

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Package RWeka updated to version 0. An R interface to Weka Version 3. Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Both the R interface and Weka itself are contained in the RWeka package.

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