Title: Modelling dependence with multivariate Archimax (or any
Description: Archimax copulas are mixture of Archimedean and EV copulas. The package provides definitions of several parametric families of generator and dependence function, computes CDF and PDF, estimates parameters, tests for goodness of fit, generates random sample and checks copula properties for custom constructs. In 2-dimensional case explicit formulas for density are used, in the contrary to higher dimensions when all derivatives are linearly approximated. Several non-archimax families (normal, FGM, Plackett) are provided as well.

Title: Modelling Dependence with Multivariate Archimax (or any

Description: Package for time series analysis of count data

Description: Time series analysis of count data

Description: Analysis of count data exhibiting autoregressive properties, using the Autoregressive Conditional Poisson model (ACP(p,q)) proposed by Heinen (2003).

Title: Engine for Acronyms and Initialisms
Authors@R: c(person("VP", "Nagraj", role = c("aut", "cre"), email = "nagraj@nagraj.net"))
Description: A tool for generating acronyms and initialisms from arbitrary text input.
Imports: magrittr, R.utils, dplyr, purrr, readr, stringr, hunspell

Description: Functions for testing affine hypotheses on the regression coefficient vector in regression models with autocorrelated errors.

Title: Download and manipulate data from the US Census ACS
Maintainer: Ezra Haber Glenn <eglenn@mit.edu>
Description: Provides a general toolkit for downloading, managing, and
analyzing data from the U.S. Census American Community Survey
(ACS) dataset.  Confidence intervals provided with the data are
converted to standard errors to be bundled with estimates in
complex acs objects.  Package provides new methods to conduct
standard operations and tests of significance on acs objects in
statistically appropriate ways.  Current version is 0.5 +/-

Title: Download and manipulate data from the US Census American
Author: Ezra Haber Glenn <eglenn@mit.edu>
(ACS).  Confidence intervals provided with the data are
statistically appropriate ways. Current version is 0.8 +/- .12.