interp.cdf

Vector of percentiles (expressed as percents) at which the
CDF values are to be interpolated.

pctval

Vector of CDF estimates in terms of proportions.

cdfest.p

Vector of CDF values to be interpolated.

cdf.value

This function interpolates CDF values at a set of percentiles. The CDF
values can be CDF estimates, CDF confidence bound estimates, or values at
which the CDF is estimated (i.e., x-axis values). It is assumed that
arguments cdfest.p and cdf.value are strictly increasing.

These functions provide procedures for selecting sites for spatial
surveys using spatially balanced algorithms applied to discrete points,
linear networks, or polygons. The probability survey designs available
include independent random samples, stratified random samples, and unequal
probability random samples (categorical or probability proportional to
size). Design-based estimation based on the results from surveys is
available for estimating totals, means, quantiles, CDFs, and linear models.
The analyses rely on package survey for most results. Variance estimation
options include a local neighborhood variance estimator that is appropriate
for spatially-balanced survey designs. A reference for the survey design
portion of the package is: D. L. Stevens, Jr. and A. R. Olsen (2004),
"Spatially-balanced sampling of natural resources.", Journal of the American
Statistical Association 99(465): 262-278, <DOI:10.1198/016214504000000250>.
Additional helpful references for this package are A. R. Olsen, T. M.
Kincaid, and Q. Payton (2012) and T. M. Kincaid and A. R. Olsen (2012), both
of which are chapters in the book "Design and Analysis of Long-Term
Ecological Monitoring Studies" (R. A. Gitzen, J. J. Millspaugh, A. B.
Cooper, and D. S. Licht (eds.), Cambridge University Press, New York,
<Online ISBN:9781139022422>).

interp.cdf: Interpolate CDF Values at a Set of Percentiles

Description

Usage

Arguments

Value