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bda (version 1.2.7-31)

Algorithms for Binned/Weighted Data Analysis

Description

This package collects functions and algorithms developed for pre-binned and weighted data analyses.

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Version

Install

install.packages('bda')

Monthly Downloads

1,010

Version

1.2.7-31

License

Unlimited

Maintainer

Bin Wang

Last Published

July 31st, 2012

Functions in bda (1.2.7-31)

mediation.test

The Sobel mediation test
getbdata

Birth data anaylysis.
histospline

Fit smoothed KDE to binned data.
birth

Birth data
biased

Biasing Functions
ofc

occipitofrontal head circumference data
rsimpson

The simpson (claw) distribution.
bootkde

To compute a bootstrap kernel density estimate
lprde

Density estimation via local polynomial regression
histo

Draw histogram based on data with rounding errors
bandwidth

Bandwidth Selectors for Kernel Density Estimation for Weighted Data
tkde

Compute Transformation-Based Kernel Density Estimate
gof

To perform goodness-of-fit test.
mle.gamma

Compute the MLEs of a gamma distribution.
zr

occipitofrontal head circumference data
rounding

Data rounding.
pcb

To compute the pointwise confidence bands.
lpreg

Local polynomial regression
perm

To perform a permutation test to compare two samples/populations.
binning

Data prebinning
edf

To compute the empirical distribution function.
pmixnorm

The mixed normal distribution
bfmm

To fit a finite mixture model to binned data.
mle.weibull

Compute the MLEs of a weibull distribution.
smkde

Fit smoothed KDE to binned data.
wkde

Compute a Binned Kernel Density Estimate for Weighted Data
histolpr

Fit smoothed KDE to binned data.