HCEB.moran: Global Heteroscedasticity-Consistent Empirical Bayes Moran's...
In phjung/HCEB: Heteroscedasticity-Consistent Empirical Bayes Rate and Spatial Autocorrelation
Description
Usage
Arguments
References
Description
Compute Global HC-EB Moran's I. Global Moran's I of areal prevalence rates with uncertainty in denominator.
Usage
1
HCEB.moran(n, x, se, listw, zero.policy = NULL)
Arguments
n
a numeric vector of counts of cases (numerator)
x
a numeric vector of populations at risk (denominator)
se
a numeric vector of sampling standard errors of corresponding populations at risk
listw
a listw object created for example by nb2listw
zero.policy
default NULL, use global option value; if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA
References
Jung, PH, Thill J-C, Issel M 2018 Spatial Autocorrelation Statistics of Areal Prevalence Rates under High Uncertainty in Denominator Data, Geographical Analysis
phjung/HCEB documentation built on May 27, 2019, 1:07 a.m.
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Description Usage Arguments References
Description
Compute Global HC-EB Moran's I. Global Moran's I of areal prevalence rates with uncertainty in denominator.
Usage
1 | HCEB.moran(n, x, se, listw, zero.policy = NULL)
|
Arguments
n |
a numeric vector of counts of cases (numerator) |
x |
a numeric vector of populations at risk (denominator) |
se |
a numeric vector of sampling standard errors of corresponding populations at risk |
listw |
a listw object created for example by nb2listw |
zero.policy |
default NULL, use global option value; if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA |
References
Jung, PH, Thill J-C, Issel M 2018 Spatial Autocorrelation Statistics of Areal Prevalence Rates under High Uncertainty in Denominator Data, Geographical Analysis
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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