pollution


The total age adjusted mortality rate, our response variable,  for the years 1959-1961. 
The data from the U.S. covers 201 Standard Metropolitan Statistical Areas (SMSA).


datasets

Engines for cross-validation of many types of regression and class prediction models are provided. These engines include built-in support for 'glmnet', 'lars', 'plus', 'MASS', 'rpart', 'C50' and 'randomforest'. It is easy for the user to add other regression or classification algorithms. The 'parallel' package is used to improve speed. Several data generation algorithms for problems in regression and classification are provided.

A.I. McLeod

gencve

General Cross Validation Engine

pollution function

A data frame with 60 observations on the following 16 variables.
  <dl>
    <dt><code>PREC</code></dt><dd>Average annual precipitation in inches</dd> <dt><code>JANT</code></dt><dd>Average January temperature in degrees F</dd> <dt><code>JULT</code></dt><dd>Average January temperature in degrees F</dd> <dt><code>OVR65</code></dt><dd>Percent of 1960 SMSA population aged 65 or older</dd> <dt><code>POPN</code></dt><dd>Average household size</dd> <dt><code>EDUC</code></dt><dd>Median school years completed by those over 22</dd> <dt><code>HOUS</code></dt><dd>Percent of housing units which are sound and with all facilities</dd> <dt><code>DENS</code></dt><dd>Population per sq. mile in urbanized areas, 1960</dd> <dt><code>NONW</code></dt><dd>Percent non-white population in urbanized areas, 1960</dd> <dt><code>WWDRK</code></dt><dd>Percent employed in white collar occupations</dd> <dt><code>POOR</code></dt><dd>Percent of families with income less than 3000 USD</dd> <dt><code>HC</code></dt><dd>Relative hydrocarbon pollution potential</dd> <dt><code>NOX</code></dt><dd>Relative nitric oxides pollution potential</dd> <dt><code>SOx</code></dt><dd>Relative sulphur pollution potential</dd> <dt><code>HUMID</code></dt><dd>Annual average percent relative humidity at 1pm</dd> <dt><code>MORT</code></dt><dd>Total age-adjusted mortality rate per 100,000</dd> </dl> 

pollution: Pollution Data from McDonald and Schwing

Description

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Examples