Spectral Density Estimation and Comparison for Functional Time Series (ftsspec)
Functions for estimating spectral density operator of functional time series (FTS) and comparing the spectral density operator of two functional time series, in a way that allows detection of differences of the spectral density operator in frequencies and along the curve length.
Quantile Classifier (quantileDA)
Code for centroid, median and quantile classifiers.
Preparing Experimental Data for Statistical Analysis (prepdat)
Prepares data collected in an experimental design for statistical analysis (e.g., analysis of variance ;ANOVA) by taking the individual data files and preparing one table that contains several possibilities for dependent variables. Most suitable when measuring reaction-times and/or accuracy, or any other variable in an interval or ratio scale. Functions included: file_merge(), read_data() and prep(). The file_merge() function vertically merges individual data files (in a long format) in which each line is a single trial within the experiment to one single dataset. The read_data() function reads a file in a txt or csv format that contains a single dataset in a long format table and creates a data frame from it. The prep() function aggregates the single dataset according to any combination of between and within grouping variables (i.e., between-subjects and within-subjects independent variables, respectively), and returns a data frame with a number of dependent measures for further analysis for each experimental cell according to the combination of provided grouping variables. Dependent measures for each experimental cell include among others means before and after rejecting all values according to a flexible standard deviation criterion/s, number of rejected values according to the flexible standard deviation criterion/s, proportions of rejected values according to the flexible standard deviation criterion/s, number of values before rejection, means after rejecting values according to procedures described in Van Selst & Jolicoeur (1994) (suitable when measuring reaction-times), standard deviations, medians, means according to any percentile (e.g., 0.05, 0.25, 0.75, 0.95) and harmonic means. The data frame prep() returns can also be exported as a txt file to be used for statistical analysis in other statistical programs.
Query and Install Specific Versions of Packages on CRAN (versions)
Installs specified versions of R packages hosted on CRAN and provides functions to list available versions and the versions of currently installed packages. These tools can be used to help make R projects and packages more reproducible. ‘versions’ fits in the narrow gap between the ‘devtools’ install_version() function and the ‘checkpoint’ package. devtools::install_version() installs a stated package version from source files stored on the CRAN archives. However CRAN does not store binary versions of packages so Windows users need to have RTools installed and Windows and OSX users get longer installation times. ‘checkpoint’ uses the Revolution Analytics MRAN server to install packages (from source or binary) as they were available on a given date. It also provides a helpful interface to detect the packages in use in a directory and install all of those packages for a given date. ‘checkpoint’ doesn’t provide install.packages-like functionality however, and that’s what ‘versions’ aims to do, by querying MRAN. As MRAN only goes back to 2014-09-17, ‘versions’ can’t install packages from before this date.
R Packages worth a look
05 Monday Oct 2015
Posted R Packages
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