# uscrime: U.S. Crime rates per 100,00 people In nipals: Principal Components Analysis using NIPALS or Weighted EMPCA, with Gram-Schmidt Orthogonalization

## Description

U.S. Crime rates per 100,00 people for 7 categories in each of the 50 U.S. states in 1977.

## Usage

 `1` ```uscrime ```

## Format

A data frame with 50 observations on the following 8 variables.

state

U.S. state

murder

murders

rape

rapes

robbery

robbery

assault

assault

burglary

burglary

larceny

larceny

autotheft

automobile thefts

## Details

There are two missing values.

## Source

Documentation Example 3 for PROC HPPRINCOMP. http://documentation.sas.com/api/docsets/stathpug/14.2/content/stathpug_code_hppriex3.htm?locale=en

## References

SAS/STAT User's Guide: High-Performance Procedures. The HPPRINCOMP Procedure. http://support.sas.com/documentation/cdl/en/stathpug/67524/HTML/default/viewer.htm#stathpug_hpprincomp_toc.htm

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17``` ```library(nipals) head(uscrime) # SAS deletes rows with missing values dat <- uscrime[complete.cases(uscrime), ] dat <- as.matrix(dat[ , -1]) m1 <- nipals(dat) # complete-data method # Traditional NIPALS with missing data dat <- uscrime dat <- as.matrix(dat[ , -1]) m2 <- nipals(dat, gramschmidt=FALSE) # missing round(crossprod(m2\$loadings),3) # Prin Comps not quite orthogonal # Gram-Schmidt corrected NIPALS m3 <- nipals(dat, gramschmidt=TRUE) # TRUE is default round(crossprod(m3\$loadings),3) # Prin Comps are orthogonal ```

nipals documentation built on Sept. 16, 2021, 1:07 a.m.