Title: The Skillings-Mack Test Statistic for Block Designs with Missing
Description: A generalization of the statistic used in Friedman's ANOVA method and in Durbin's rank test. This nonparametric statistical test is useful for the data obtained from block designs with missing observations occurring randomly. A resulting p-value is based on the chi-squared distribution and Monte Carlo method.
Packaged: 2015-09-25 09:16:59 UTC; Patchanok

Description: Provides an alternative to manually process hemispherical pictures. The algorithm processes each picture one by one to determine the proportion of sky pixel. The algorithm uses the Ridler and Calvard method (Ridler and Calvard 1978).
Packaged: 2016-02-03 22:42:12 UTC; benedicte

Author: Ali Santacruz, SkyWatch API Developers
Description: Query and download satellite imagery and climate/atmospheric datasets using the SkyWatch API.
Search datasets by wavelength (band), cloud cover, resolution, location, date, etc.
Get the query results as data frame and as HTML. To learn more about the SkyWatch API, see <https://github.com/skywatchspaceapps/api>.
Depends: R (>= 2.14.0), httr, htmlTable, sp, methods

Title: Search and Download Satellite Imagery using the SkyWatch API

Title: Pathway Testing for Longitudinal Omics
Description: A self-contained hypothesis is tested for a given pathway of longitudinal omics. 'SlaPMEG' is a two-step procedure. First, a shared latent process mixed model is fitted over the longitudinal measures of omics in a pathway. This shared model allows deviation from the shared process at subject level (a random intercept, slope, or both per subject) and also at omic level (a random effect per omic). These random effects summarize the longitudinal trend of the observations which can be used to test for group differences using 'Globaltest' in the second step. If the pathway is large or the shared effect is small, the package fits a series of pairwise models and estimates the shared random effects based on them.
Packaged: 2020-09-15 19:37:47 UTC; mebrahimpoor