Functions to easily return simulated predicted probabilities and
first differences for multinomial logit models. It takes a specified
scenario and a multinomial model to predict probabilities with a set of
coefficients, drawn from a simulated sampling distribution. The simulated
predictions allow for meaningful plots with means and confidence intervals.
The methodological approach is based on the principles laid out by King,
Tomz, and Wittenberg (2000) <doi:10.2307/2669316> and Hanmer and Ozan Kalkan
(2016) <doi:10.1111/j.1540-5907.2012.00602.x>.
knitr, rmarkdown, testthat, nnet, magrittr, ggplot2, scales

person(given = "Manuel",
family = "Neumann",
role = c("aut", "cre"),
email = "manuel.neumann@mzes.uni-mannheim.de",
comment = c(ORCID = "0000-0002-7953-3939"))
Manuel Neumann [aut, cre] (<https://orcid.org/0000-0002-7953-3939>)

Multivariate Nonparametric Methods. An Approach Based on Spatial
Signs and Ranks
Klaus Nordhausen, Jyrki Mottonen, Hannu Oja
R (>= 2.9.2), ellipse, ICS, ICSNP, SpatialNP, mvtnorm, survey
The package provides multivariate tests, estimates and
methods based on the identity score, spatial sign score and
spatial rank score. The methods include one and c-sample
problems, shape estimation and testing, linear regression and
principal components.

The package provides multivariate tests, estimates and methods based on the identity score, spatial sign score and spatial rank score. The methods include one and c-sample problems, shape estimation and testing, linear regression and principal components.

Multivariate tests, estimates and methods based on the identity score, spatial sign score and spatial rank score are provided. The methods include one and c-sample problems, shape estimation and testing, linear regression and principal components.

Multivariate tests, estimates and methods based on the identity score, spatial sign score and spatial rank score are provided. The methods include one and c-sample problems, shape estimation and testing, linear regression and principal components. The methodology is described in Oja (2010) <doi:10.1007/978-1-4419-0468-3> and Nordhausen and Oja (2011) <doi:10.18637/jss.v043.i05>.