WACSestim {WACS}

Estimation of the parameters of a WACS model

Description

Estimation of the parameters of a WACS model

Usage

WACSestim(
  wacsdata,
  spar = 0.7,
  trend.norm = "L2",
  rain.model = "Gamma",
  method = "MLE",
  Vsel = NULL,
  Nclusters = NULL,
  clustering = "soft",
  plot.it = FALSE,
  DIR = "./"
)

Arguments

wacsdata

Data, as returned by WACSdata

spar

Smoothing parameter for estimating annual cycle

trend.norm

Type of norm used in for computing central tendency and variation. Must be "L1" or "L2".

rain.model

Model for precipitation. Must be "Gamma" or "None"

method

"MLE" or "MOM". Estimation method for the rain model.

Vsel

Variables (other than rain) on which clustering is performed when Vsel=NULL, all variables are considered.

Nclusters

Number of clusters to consider. When Nclusters = NULL, absolute best clustering is sought for wet and dry weather states in each season (up to 4).

clustering

Indicates whether "hard" or "soft" clustering is considered.

plot.it

Boolean indicating whether plots are produced

DIR

Directory in which placing plot

Value

A list containing all parameters; see the user guide for details.

Note

Larger values of spar produce smoother estimates. Smaller values produce less smooth estimates. spar=0.7 is a good compromise

Soft clustering means that days have probabilities to belong to each weather state. With hard clustering, this probability is set to 1 to the most likely weather state and 0 to all others. Density parameter estimates are more robust with clustering="soft". Clustering is done by means of the mclust package with modelNames="VVV"

Examples

## Not run: 

 ## For an estimation with default setting 
 ThisPar  = WACSestim(ThisData)

 ## For an estimation with max. 2 dry and wet weather types per season, 
 ## and production of plots
 ThisPar  = WACSestim(ThisData, Nclusters = 1:2, plot.it = TRUE) 

 ## For an estimation with exactly 2 dry and wet weather states per season, 
 ## clustering on variables 3 and 5 only and no production of plots
 ThisPar  = WACSestim(ThisData, Nclusters = 2, Vsel = c(3,5)) 
 
## End(Not run)