Arguments agdex.result agdex result returned by function agdex gset.ids a vector of gene-set IDs. If NULL, the result will return gene level details for all significant gene-sets at a chosen significant level alpha. alpha significance level of gene-set, default set to 0.01

Arguments. Xxxx.xxxx an ExpressionSet object carries the gene expression data (Exprs) and Phenotype data (pData) comp.var the column name or numeric index for group labels in pData of object Xxxx.xxxx xxxx.xxx a string definition of comparison, group labels connected by "-" gset.collection an object belongs to class GeneSetCollection Details The ExpressionSet includes two components: exprs: a matrix of expression values pData: a data frame contains the sample IDs and their assigned group labels. gset.collection contains a GeneSetCollection object defined in the Bioconductor package GSEABase. The gset.collection object must use the same identifiers for probe-sets as that used in the exprs com- ponent of Xxxx.xxxx.

Arguments data a matrix of scores. Each row corresponds to a unit, each column a coder. level the level of measurement, one of "nominal", "ordinal", "interval", or "ratio"; or a user-defined distance function. confint logical; if TRUE, a bootstrap sample is produced. verbose logical; if TRUE, various messages are printed to the console. Note that if confint = TRUE a progress bar (pblapply) is displayed (if possible) during the bootstrap computation. control a list of control parameters. bootit the size of the bootstrap sample. This applies when confint = TRUE. Defaults to 1,000. nodes the desired number of nodes in the cluster. parallel logical; if TRUE (the default), bootstrapping is done in parallel. type one of the supported cluster types for makeCluster. Defaults to "SOCK".

Arguments x an object of class "krippendorffsalpha", the result of a call to krippendorffs.alpha. y always ignored. level the desired confidence level for the interval. The default is 0.95. type the method used to compute sample quantiles. This argument is passed to quantile. The default is 7. density logical; if TRUE, a kernel density estimate is plotted. lty.density the line type for the kernel density estimate. The default is 1. lty.estimate the line type for the estimate of alpha. The default is 1. lty.interval the line type for the confidence limits. The default is 2. col.density the color for the kernel density estimate. The default is black. col.estimate the color for the estimate of alpha. The default is orange. col.interval the color for the confidence limits. The default is blue. lwd.density the line width for the kernel density estimate. The default is 3. ratio.dist 9 lwd.estimate the line width for the estimate of alpha. The default is 3. lwd.interval the line width for the confidence limits. The default is 3.

Argumentsmodel a fitted model object, the result of a call to krippendorffs.alpha. units a vector of integers. A DFBETA will be computed for each of the corresponding units. coders a vector of integers. A DFBETA will be computed for each of the corresponding coders. ... additional arguments. These are ignored.

Arguments. 5. In January 2013, the EPO and the Republic of Moldova reached agreement on the text of a validation agreement, including an attachment containing model provisions fornational implementation of the validation system.

Arguments rankMat A matrix with k columns corresponding to the k ranked lists. Elements of each column are integers between 1 and the length of the lists maxlength The maximum depth that are needed XXX B The number of resamples to use in the presence of censored lists cens A vector of integer values that type The type of distance measure to use: 0 (the default) is the variance while 1 is MAD (median absolute deviation) epsilon A non-negative numeric vector that contains the minimum limit in proportion of lists that must show the item. Defaults to 0. If a single number is provided then the value will be recycles to the number of items.