precip_hydroMet: Make homogeneity test or fill gaps in a series

In hydroToolkit: Hydrological Tools for Handling Hydro-Meteorological Data from Argentina and Chile

Description

This method can do both: test homogeneity in precipitation series or fill data gaps using regional analysis.

Usage

precip_hydroMet(
  obj,
  col_target = 2,
  fill = FALSE,
  method = "spearman",
  min_value = 0.2
)

## S4 method for signature 'hydroMet_compact'
precip_hydroMet(
  obj,
  col_target = 2,
  fill = FALSE,
  method = "spearman",
  min_value = 0.2
)

Arguments

obj	an hydroMet_compact class object.
col_target	numeric. The column number of the target series (either to test homogeneity or to fill gaps) in compact slot.
fill	logical. By default value (FALSE) you will make an homogeneity test to your target series.
method	string (default is spearman - possible values are: spearman, pearson or kendall). When creating the regional (or master series) the method uses a weighted mean. The weighted values are the correlations coefficients.
min_value	numeric. Series with a correlation value less than min_value are thrown away.

Value

If fill = FALSE the method will return a list with three elements: a data frame with all necessary values to correct your target serie, a plot with p-values and the correlation matrix. When fill = TRUE the list will contain: the data frame with the target series gaps filled and the correlation matrix.

Functions

• precip_hydroMet,hydroMet_compact-method: homogeneity test applied to precipitation data stored in compact class.

Examples

# Load daily precipitation data-set from BDHI
load( paste0(system.file('extdata', package = "hydroToolkit"), '/bdhi_p.rda') )

# Fill gaps in Tupungato station
relleno <- precip_hydroMet(obj = bdhi_p, col_target = 5, fill = TRUE)

hydroToolkit documentation built on July 2, 2020, 1:04 a.m.