Multivariate weather generator for daily climate variables based on weather-states using a Markov chain for modeling the succession of weather states. Conditionally to the weather states, the multivariate variables are modeled using the family of Complete Skew-Normal distributions. Parameters are estimated on measured series. Data must include the variable 'Rain' and can accept as many other variables as desired.
|Author||Denis Allard [aut, cre], Ronan Trepos [aut]|
|Date of publication||2016-02-25 18:03:23|
|Maintainer||Denis Allard <firstname.lastname@example.org>|
|License||GPL (>= 2.0)|
ClimateSeries: Synthetic climate series of a french town between 1995 and...
WACS: WACS: Multivariate Weather-state Approach Conditionally...
WACScompare: Performs comparisons between two WACS data structures, or...
WACSdata: Format data for WACS
WACSestim: Estimation of the parameters of a WACS model
WACSplot: Produces validation and/or WACS comparison plots
WACSplotdensity: For plotting fitted bivariate densities of residuals
WACSreadAgroclim: Function that reads a file of format Agroclim
WACSsimul: Performs simulations based on estimated parameters of the...
WACSvalid: Performs validations of WACS simulations
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