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keywords: iteration
title: Auxiliary for Controlling BRGLM Fitting
description: Auxiliary function as user interface for brglm fitting. Typically only used when calling brglm or brglm.fit.

keywords: iteration
title: Auxiliary for Controlling BRGLM Fitting
description: Auxiliary function as user interface for brglm fitting. Typically only used when calling brglm or brglm.fit.

keywords: iteration
title: Do Things Repeatedly
description: do() provides a natural syntax for repetition tuned to assist with replication and resampling methods.

keywords: iteration
title
description: Auxiliary function as user interface for mbrglm fitting. Typically only used when calling mbrglm or mbrglm.fit.

keywords: iteration
title: Get indices for partial image reading/writing
description: In the case of 'Cannot allocate vector of size ...' error message chunk_band returns list of bands indices, which are suitable for allocation in memory at once, chunk_line returns list of lines (rows) indices, which are suitable for allocation in memory at once. chunk_expand is used to expand lines indices and can by applied in focal functions.

keywords: iteration
title: Forecastable Component Analysis
description: foreca performs Forecastable Component Analysis (ForeCA) on \(\mathbf{X}_t\) -- a \(K\)-dimensional time series with \(T\) observations. Users should only call foreca, rather than foreca.one_weightvector or foreca.multiple_weightvectors. foreca.one_weightvector is a wrapper around several algorithms that solve the ForeCA optimization problem for a single weightvector \(\mathbf{w}_i\) and whitened time series \(\mathbf{U}_t\). foreca.multiple_weightvectors applies foreca.one_weightvector iteratively to \(\mathbf{U}_t\) in order to obtain multiple weightvectors that yield most forecastable, uncorrelated signals.

keywords: iteration
title: Iteratively Estimate Population Parameters and Genotypes In a Diversity Panel
description: These are wrapper function that iteratively run other polyRAD functions until allele frequencies stabilize to within a user-defined threshold. Genotype posterior probabilities can then be exported for downstream analysis.

keywords: iteration
title: Apply a Function over values in a flowSet
description: fsApply like many of the apply-style functions in R acts as an iterator for flowSet objects, allowing the application of a function to either the flowFrame or the data matrix itself. The output can the be reconstructed as either a flowSet, a list or a matrix depending on options and the type of objects returned.

keywords: iteration
title: mice: Multivariate Imputation by Chained Equations
description: The mice package implements a method to deal with missing data. The package creates multiple imputations (replacement values) for multivariate missing data. The method is based on Fully Conditional Specification, where each incomplete variable is imputed by a separate model. The MICE algorithm can impute mixes of continuous, binary, unordered categorical and ordered categorical data. In addition, MICE can impute continuous two-level data, and maintain consistency between imputations by means of passive imputation. Many diagnostic plots are implemented to inspect the quality of the imputations. Generates Multivariate Imputations by Chained Equations (MICE)