Provides the spatial sign correlation and the two-stage spatial sign correlation as well as a one-sample test for the correlation coefficient.

It helps in determination of sample size for estimation of population mean and proportion based upon the availability of prior information on coefficient of variation (CV) of the population under Simple Random Sampling (SRS) with or without replacement sampling design. If there is no prior information on the population CV, then a small preliminary sample of size is selected to estimate the population CV which is then used for determination of final sample size. If the final sample size is more than the preliminary sample size, then the preliminary sample is augmented by drawing additional units from the remaining population units so that the size of the augmented sample is equal to the final sample size. On the other hand, if the preliminary sample size is larger than the final sample size, then the preliminary sample is considered as the final sample.

Web application using 'shiny' for the SSD (Species
    Sensitivity Distribution) module of the MOSAIC (MOdeling and
    StAtistical tools for ecotoxICology) platform. It estimates the
    Hazardous Concentration for x% of the species (HCx) from toxicity
    values that can be censored and provides various plotting options for
    a better understanding of the results. See our companion paper
    Kon Kam King et al. (2014) <doi:10.48550/arXiv.1311.5772>.

Reference data sets of species sensitivities to compare the 
    results of fitting species sensitivity distributions 
    using software such as 'ssdtools' and 'Burrlioz'. 
    It consists of 17 primary data sets from
    four different Australian and Canadian organizations as well as five
    datasets from anonymous sources. It also includes a data set of the
    results of fitting various distributions using different software.

Functions to visually and statistically analyze single system data.

Allows to map species richness and endemism based on stacked
    species distribution models (SSDM). Individuals SDMs can be created using a
    single or multiple algorithms (ensemble SDMs). For each species, an SDM can
    yield a habitat suitability map, a binary map, a between-algorithm variance
    map, and can assess variable importance, algorithm accuracy, and between-
    algorithm correlation. Methods to stack individual SDMs include summing
    individual probabilities and thresholding then summing. Thresholding can be
    based on a specific evaluation metric or by drawing repeatedly from a Bernoulli
    distribution. The SSDM package also provides a user-friendly interface.