Permutation Tests (wPerm)
Supplies permutation-test alternatives to traditional hypothesis-test procedures such as two-sample tests for means, medians, and standard deviations; correlation tests; tests for homogeneity and independence; and more. Suitable for general audiences, including individual and group users, introductory statistics courses, and more advanced statistics courses that desire an introduction to permutation tests.
Accuracy and Precision of Measurements (merror)
N>=3 methods are used to measure each of n items. The data are used to estimate simultaneously systematic error (bias) and random error (imprecision). Observed measurements for each method or device are assumed to be linear functions of the unknown true values and the errors are assumed normally distributed. Maximum likelihood estimation is used for the imprecision standard deviation estimates. Pairwise calibration curves and plots can be easily generated.
Three-Way Data Analysis Through Densities (dad)
The three-way data consists of a set of variables measured on several groups of individuals. To each group is associated an estimated probability density function. The package provides functional methods (principal component analysis, multidimensional scaling, discriminant analysis…) for such probability densities.
Community Dynamics Metrics (codyn)
A toolbox of ecological community dynamics metrics that are explicitly temporal. Functions fall into two categories: temporal diversity indices and community stability metrics. The diversity indices are temporal analogs to traditional diversity indices such as richness and rank-abundance curves. Specifically, functions are provided to calculate species turnover, mean rank shifts, and lags in community similarity between time points. The community stability metrics calculate overall stability and patterns of species covariance and synchrony over time.
Generalized Method of Wavelet Moments (gmwm)
Generalized Method of Wavelet Moments (GMWM) is an estimation technique for the parameters of time series models. It uses the wavelet variance in a moment matching approach that makes it particularly suitable for the estimation of certain state-space models. Furthermore, there exists a robust implementation of GMWM, which allows the robust estimation of some state-space models and ARIMA models. Lastly, the package provides the ability to quickly generate time series data, perform different wavelet decompositions, and visualizations.