| prostate_cancer {spGARCH} | R Documentation |
Logarithmic incidence rates of prostate cancer and covariates
Description
The dataset contains logarithmic incidence rates from the National Cancer Institute and Centers for Disease, Control and Prevention (State Cancer Profiles) and factor loadings of a set of covariates. The incidence rates are 5-year averages from 2008 to 2012 in several southeastern states (Arkansas, Louisiana, Mississippi, Tennessee, North and South Carolina, Georgia, Alabama, and Florida). Missing values were imputed by spatial averaging.
Usage
data("prostate_cancer")
Format
A list with three entries:
dataa data frame; see below for details
Ba numeric matrix; weighting matrix B to run the example
Wa numeric matrix; weighting matrix W to run the example
The data frame contains 755 observations of the following 12 variables.
log_incidence_ratesa numeric vector; logarithmic incidence rates of prostate cancer
F_1a numeric vector; scores of factor 1 (environment: fine atmospheric particles and aerosols)
F_2a numeric vector; scores of factor 2 (environment: particulate matter)
F_3a numeric vector; scores of factor 3 (weather: solar radiation and temperature)
F_4a numeric vector; scores of factor 4 (weather: temperature differences)
F_5a numeric vector; scores of factor 5 (behavior: smoking)
F_6a numeric vector; scores of factor 6 (behavior: drinking)
F_7a numeric vector; scores of factor 7 (behavior: preventive health care)
F_8a numeric vector; scores of factor 8 (behavior: physical activity)
F_9a numeric vector; scores of factor 9 (health: overweight)
F_10a numeric vector; scores of factor 10 (health: cholesterol and blood pressure)
PSA_testa numeric vector; percentage of positive results for a prostate-specific antigen (PSA) test
Source
https://statecancerprofiles.cancer.gov/index.html
National Cancer Institute, Centers for Disease, Control and Prevention
References
https://statecancerprofiles.cancer.gov/map/map.withimage.php?99&001&001&00&0&02&0&1&10 Otto, P. (2019). spGARCH: An R-Package for Spatial and Spatiotemporal ARCH and GARCH models To appear: The R Journal URL: https://arxiv.org/abs/1812.01871
Examples
data(prostate_cancer)
## Not run:
# Estimation (long running example)
formula <- "log_incidence_rates ~ F_2 + F_10"
out <- qml.SARspARCH(formula, B = prostate_cancer$B, W = prostate_cancer$W,
type = "spARCH", data = prostate_cancer$data)
# Summary
summary(out)
## End(Not run)