npsp internal and secondary functions

Share:

Description

Listed below are supporting functions for the major methods in npsp.

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
.cpu.time.ini()

.compute.masked(bin, cov.bin = NULL, tol.mask = npsp.tolerance(2))

.wloss(est, teor, w, loss = c("ASE", "ARSE", "AAE", "ARAE"))

## S3 method for class 'locpol.bin'
residuals(object, ...)

## S3 method for class 'grid.par'
print(x, ...)

## S3 method for class 'grid.par'
dim(x)

## S3 method for class 'grid.par'
dimnames(x)

## S3 method for class 'grid.par'
as.data.frame(x, row.names = dimnames(x),
  optional = FALSE, ...)

is.data.grid(x)

## S3 method for class 'data.grid'
dim(x)

## S3 method for class 'data.grid'
dimnames(x)

splot.plt(horizontal = FALSE, legend.shrink = 0.9, legend.width = 1,
  legend.mar = ifelse(horizontal, 3.1, 5.1), bigplot = NULL,
  smallplot = NULL)

.rev.colorRampPalette(colors, interpolate = "spline", ...)

Arguments

cov.bin

(optional) covariance matrix of the binned data or semivariogram model (svarmod-class) of the (unbinned) data.

Value

.compute.masked returns a list with components:

mask

logical vector bin$binw > tol.mask.

w

x$binw[mask].

sw

sum(w).

hat

(optional) bin$locpol$hat[mask, mask].

cov.bin

(optional) masked (aproximated) covariance matrix of the binned data.

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.