General purpose TIFF file I/O for R users.  Currently the
    only such package with read and write support for TIFF files with
    floating point (real-numbered) pixels, and the only package that can
    correctly import TIFF files that were saved from 'ImageJ' and write
    TIFF files than can be correctly read by 'ImageJ'
    <https://imagej.net/ij/>. Also supports text image I/O.

Simple handling of survey data. Smart handling of meta-information like e.g. variable-labels value-labels and scale-levels. Easy access and validation of meta-information. Useage of value labels and values respectively for subsetting and recoding data.

Convert irregularly spaced longitudinal data into regular intervals for further analysis, 
             and perform clustering using advanced machine learning techniques. 
             The package is designed for handling complex longitudinal datasets, 
             optimizing them for research in healthcare, demography, and other fields 
             requiring temporal data modeling.

It performs interlaboratory studies (ILS) to detect those
    laboratories that provide non-consistent results when comparing to others. It
    permits to work simultaneously with various testing materials, from standard
    univariate, and functional data analysis (FDA) perspectives. The univariate
    approach based on ASTM E691-08 consist of estimating the Mandel's h and
    k statistics to identify those laboratories that provide more significant
    different results, testing also the presence of outliers by Cochran and Grubbs
    tests, Analysis of variance (ANOVA) techniques are provided (F and Tuckey
    tests) to test differences in means corresponding to different laboratories per
    each material. Taking into account the functional nature of data retrieved in
    analytical chemistry, applied physics and engineering (spectra, thermograms,
    etc.). ILS package provides a FDA approach for finding the Mandel's k and h
    statistics distribution by smoothing bootstrap resampling.