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SciencesPo (version 1.3.7)

A Tool Set for Analyzing Political Behavior Data

Description

Provides miscellaneous functions for carrying out political behaviour analysis, including measures of political fragmentation, seats allocation, and graphical demonstrations.

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Version

Install

install.packages('SciencesPo')

Monthly Downloads

45

Version

1.3.7

License

GPL (>= 2)

Maintainer

Daniel Marcelino

Last Published

August 13th, 2015

Functions in SciencesPo (1.3.7)

Add Error Bars on the Graph

A Tool Set For Analyzing Political Behavior Data

Identify columns with at least one NA value and fill with the mean value

Geary's test for normality

Count NA values

Anscombe-Glynn test of kurtosis

Calculates the Standard Error

Generate Markov Chains

politicalDiversity

Political Diversity Indices politicalDiversity is used to analyze political diversity in a unity or across them. It provides methods to estimate the Effective Number of Parties as well as other diversity measures.

Method for Bootstrap

Method for adding things.

Cross-tabulation

Mishkin's (1992) Data

Christensen's and Greene's (1976) Data

Dirichlet distribution

Binomial cumulative distribution function

Plot Markov Chains

fill NA by previous cell value (fill forward)

Marc Nerlove's (1963) data

Gallagher index

Jensen-Shannon Distance

Frequency table

Simulates a Levy Walk

Move variable order in a data.frame

Random Imputation

Pearson's Coefficient of Variation

Generate dummy variables

Add Footnote to a ggplot Object

Aggregate a numeric variable

Detect Outliers

Trim white spaces

Rownames to column

Create k random permutations of a vector

Stukel's test of the logistic link

View random n elements of an object.

NY Weather 1995-2014

Galton's Family Data on Human Stature.

Converts integer into its Roman Numeral equivalent

Unnest a Nested List

Scale colors for ggplot graphs

Extraction of categorical values as a preprocessing step for making dummy variables

Method for Roc Analysis

Find Matching (or Non-Matching) Elements

James-Stein shrunken estimates

Method for renaming

Flag duplicated observations

Multiple ggplot objects

Compute the Kurtosis

Arrange multiple ggplot objects

Unity-based normalization

Add quotation marks

Seat allocation and its ordering

Adjusted Residuals

Method for building things

Stock's and Watson's (1993) Data.

The Penn World Table

Join a list of data frames

Dirichlet distribution

Bekaert's and Hodrick's (1993) Data

Compute z-scores

Converts to percentiles

Calculate the Mode

Cox-Shugart measure of proportionality

Wrapper for dbConnect

Filling in missing values fillin replaces missing values with existing observations from other variable or data frame.

Winsorized Mean

Round numbers with no leading zero

Gini Simpson Index

Method for the number of observations

Statistical description

Normal Cumulative Distribution

Make a data.frame Rectangular by fill in missing records

US Presidential Election Opinion Polls

Themes for ggplot graphs

Variance Inflation Factor

Lothian's and Taylor's (1996) Data Set

D'Agostino test of skewness

Conditionally convert vectors to factors

Weighted Variance

Replace commas by dots

Lijphart index of proportionality

Watch For Changes in a Data Object

Reverse the levels of a factor.

Bonett-Seier test of Geary's kurtosis

Detach all data frame from the search path

Format numeric digits

Generate a footnote for graphs Generate a footnote for graphs

Factors to numeric

Find the Nearest Value

Fractional part of a numeric vector.

Calculates the true median

Shifts elements of a vector left or right by N positions (Lag or Lead).

Add transparency

Griliches's (1976) Data

Calculate number of permutations taking repeated elements into consideration

Inverse Cumulative Standard Normal Distribution

Normal probability density function

scale_colour_pub

Scale colors for ggplot graphs

Compute the Skewness

Same Sex Marriage Public Opinion Data

Recode very small levels into Missing values

Tobacco Lobbying Data

Converts rle object to data.frame

regionSignificance

Computes the region significance

The Hamilton method of apportionment

anderson.darling

Anderson-Darling test for normality

Confidence Intervals

Creates a temporary table in the database

Resamples Data Using the Jackknife Method

Jarque-Bera test for normality

Johnson-Neyman Regression

Modify data elements by their position

Show Observations Randomly Drawn from the Data

Reads zTree output files

Binomial probability density function

Method to Produce Descriptive Statistics Summary

Lilliefors (Kolmogorov-Smirnov) test for normality

nearestPosition

Find Location of the Nearest Value

Shades Normal Distribuion

Method for recoding

Transform dependent variable

Create Block-randomized designs