R: A combination of all the premium in the data sets on the case...
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A combination of all
R: A combination of all the premium in the data sets on the case...
premiumR Documentation
A combination of all
R: Autoregressive Conditional Poisson (ACP) Regression
acpR Documentation
Autoregressive Conditional Poisson (ACP
R: Autoregressive Conditional Poisson (ACP) Regression
acpR Documentation
Autoregressive Conditional Poisson (ACP
R: Risk Premium computation
premiumR Documentation
Risk Premium computation
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method that produces scatter plots of predicted vs observed measurements for the training set.
Value
Function WA returns
method that produces scatter plots of predicted vs observed measurements for the training set.
Value
Function WA returns
Package: PReMiuM
Type: Package
Title: Dirichlet Process Bayesian Clustering, Profile Regression
, initial = 1, window = 50)
# ACP with asymmetric nonconformity scores and rolling calibration sets
acpfc <- acp(fc
Package: WA
Type: Package
Title: While-Alive Loss Rate for Recurrent Event in the Presence of
component analysis
Usage
acp(x,center=TRUE,reduce=TRUE,wI=rep(1,nrow(x)),wV=rep(1,ncol(x)))
Description
An<c3><a1>lisis de componentes principales.
Usage
-climbing algorithm
Description
Box-constrained optimization using an iterative hill-climbing algorithm
Package: acp
Title: Autoregressive Conditional Poisson
Version: 2.1
Package: kitchen
Type: Package
Title: Convolutional Kitchen Sinks in R
R: Add, Commit, and Push
acpR Documentation
Add, Commit, and Push
of Washington.
Usage
data("WA")
mod <- wa(SumSST ~., data = ImbrieKipp)
## extract the fitted values
fitted(mod)
of Washington.
Usage
data("WA")
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