HEAT

Summer maximum and minimum temperature (degrees Fahrenheit) for July through August 1948 through 1990 at
Sky Harbor airport in Phoenix, Arizona.

datasets

General functions for performing extreme value analysis. In particular, allows for inclusion of covariates into the parameters of the extreme-value distributions, as well as estimation through MLE, L-moments, generalized (penalized) MLE (GMLE), as well as Bayes. Inference methods include parametric normal approximation, profile-likelihood, Bayes, and bootstrapping. Some bivariate functionality and dependence checking (e.g., auto-tail dependence function plot, extremal index estimation) is also included. For a tutorial, see Gilleland and Katz (2016) <doi: 10.18637/jss.v072.i08> and for bootstrapping, please see Gilleland (2020) <doi: 10.1175/JTECH-D-20-0070.1>.

Eric Gilleland

extRemes

Extreme Value Analysis

HEAT function

A data frame with 43 observations on the following 3 variables.<dl>
 <dt>Year</dt>
<dd>a numeric vector giving the number of years since 1900.</dd> <dt>Tmax</dt>
<dd>a numeric vector giving the Summer maximum temperatures in degrees Fahrenheit.</dd> <dt>Tmin</dt>
<dd>a numeric vector giving the Summer minimum temperatures in degrees Fahrenheit.</dd> 
</dl>

Format

Summer Maximum and Minimum Temperature: Phoenix, Arizona — HEAT

A data frame with 43 observations on the following 3 variables.<dl>
 <dt>Year</dt>
<dd>a numeric vector giving the number of years since 1900.</dd>

 <dt>Tmax</dt>
<dd>a numeric vector giving the Summer maximum temperatures in degrees Fahrenheit.</dd>

 <dt>Tmin</dt>
<dd>a numeric vector giving the Summer minimum temperatures in degrees Fahrenheit.</dd>

 
</dl>

HEAT: Summer Maximum and Minimum Temperature: Phoenix, Arizona

Description

Usage

Arguments

Format

Details

References

Examples