Title: Automated access to old World Fertility Survey data saved in fixed-width format based on ISI-formatted codebooks.
License: GPL (>= 2.0). Additionally, publications to which the Read.isi-package has contributed should refer to this package. Use license('Read.isi') for information on how to refer to this package.
Packaged: Thu Aug  7 11:59:18 2008; Rense

Title: Read ESA SNAP Processed Raster Format in R
Description: It helps you to read (.dim) images with CRS directly into R programming. One can import both Sentinel 1 and 2 images or any processed data with this software.

Author: Markus Loecher, Nikon Systems Inc, Nikon Digital Technologies
Description: This package provides functions for reading JPEG files,
extracted from the archived 'rimage' package.
X-CRAN-Comment: Orphaned on 2012-12-21 as the maintainer failed to
respond to requests to update it for R >= 2.14.0

Author: Andrew Karl, Jennifer Broatch, and Jennifer Green
Description: The RealVAMs package fits a multivariate value-added model (VAM) (see Broatch and Lohr 2012) with normally distributed test scores and a binary outcome indicator. This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.

Imports: numDeriv, Rcpp (>= 0.11.2), methods, stats, utils

Author: Andrew T. Karl, Jennifer Broatch, and Jennifer Green
Description: Fits a multivariate value-added model (VAM), see Broatch and Lohr (2012) <doi:10.3102/1076998610396900>, with normally distributed test scores and a binary outcome indicator. A pseudo-likelihood approach, Wolfinger (1993) <doi:10.1080/00949659308811554>, is used for the estimation of this joint generalized linear mixed model.  This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.
Imports: numDeriv, Rcpp (>= 0.11.2), methods, stats, utils, grDevices,

Description: Fits a multivariate value-added model (VAM), see Broatch and Lohr (2012) <doi:10.3102/1076998610396900>, with normally distributed test scores and a binary outcome indicator. A pseudo-likelihood approach, Wolfinger (1993) <doi:10.1080/00949659308811554>, is used for the estimation of this joint generalized linear mixed model.  The inner loop of the pseudo-likelihood routine (estimation of a linear mixed model) occurs in the framework of the EM algorithm presented by Karl, Yang, and Lohr (2013) <DOI:10.1016/j.csda.2012.10.004>. This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.