Tools to help text files importation. It can return
the number of lines; print the first and last lines; convert
encoding. Operations are made without reading the entire file
before starting, resulting in good performances with large files.
This package provides an alternative to a simple use of the
'head', 'tail', 'wc' and 'iconv' programs that are not always
available on machine where R is installed.

Given the values of sampled units and selection probabilities
the desraj function  in the package computes the estimated value of the total
as well as estimated variance.

Automatic Distribution Graphs Using Formulas
Easy way to plot common types of graphics with moderators by using formulas. The core of the package concerns distribution plots which are automatic: the many options are tailored to the data at hand to offer the nicest and most meaningful graphs possible -- with no/minimum user input.

Easy way to plot regular/weighted/conditional distributions by using formulas. The core of the package concerns distribution plots which are automatic: the many options are tailored to the data at hand to offer the nicest and most meaningful graphs possible -- with no/minimum user input. Further provide functions to plot conditional trends and boxplots.

stats, graphics, utils, Formula, Rcpp, grDevices, dreamerr(>=
1.1.0)

person("Federico", "Marotta", email = "federicomarotta@mail.com",
role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0174-3901"))
Read and process a large delimited file block by
block. A block consists of all the contiguous rows that have the same value
in the first field. The result can be saved as a list or printed to an
output file.
Federico Marotta [aut, cre] (<https://orcid.org/0000-0002-0174-3901>)

Read and process a large delimited file block by
block. A block consists of all the contiguous rows that have the same value
in the first field. The result can be returned as a list or a data.table,
or even directly printed to an output file.

person("Jaroslav", "Kuchar", email = "jaroslav.kuchar@gmail.com", role = c("aut", "cre"))
Algorithms for detection of outliers based on frequent pattern
mining. Such algorithms follow the paradigm: if an instance contains more frequent patterns,
it means that this data instance is unlikely to be an anomaly (He Zengyou, Xu Xiaofei, Huang
Zhexue Joshua, Deng Shengchun (2005) <doi:10.2298/CSIS0501103H>).
The package implements a list of existing state of the art algorithms as well as other published
approaches: FPI, WFPI, FPOF, FPCOF, LFPOF, MFPOF, WCFPOF and WFPOF.
pmml, XML, Matrix, R.utils, arules (>= 1.5-4), foreach,
doParallel, parallel, methods, pryr