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DESCRIPTION
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DESCRIPTION
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Package: kcde
Title: Kernel conditional density estimation with flexible kernel
specifications
Version: 0.0.0.9000
Authors@R: person("Evan", "Ray", , "elray@umass.edu", c("aut", "cre"))
Description: A flexible implementation of kernel conditional density estimation.
The user may specify the kernel function in terms of a product of several
component kernel functions, each of which is used for one or more variables.
Although the package functionality can be used in any context, it is
oriented toward prediction in the context of time series and handles
treatment of lagged and lead covariates. Two default kernel specifications
are provided: a periodic kernel function, and a partially discretized
truncated multivariate normal. Predictions may take the form of (1)
evaluating the predictive density, (2) point predictions [not yet
implemented], or (3) sampling from the predictive density.
Depends:
R (>= 3.0.2)
Imports:
robust,
pdtmvn,
plyr
License: GPL-3
LazyData: true
Suggests:
knitr,
testthat,
covr,
reshape,
cdcfluview,
dplyr,
lubridate,
ggplot2,
grid
URL: https://github.com/reichlab/kcde
BugReports: https://github.com/reichlab/kcde/issues
VignetteBuilder: knitr
Remotes: reichlab/pdtmvn
RoxygenNote: 5.0.1