Packaged: Sat Mar 31 11:15:50 2007; bkatzen

Packaged: Mon Aug 27 02:16:05 2007; bkatzen

Title: Computes Local False Discovery Rates
Description: Computation of local false discovery rates.

Title: Local Regression, Likelihood and Density Estimation.
Description: Local Regression, Likelihood and density estimation.
License: Free for non-commercial use, see the file COPYRIGHT for details

Packaged: Thu Sep 22 13:07:19 2005; andy

Packaged: Tue Mar 16 15:44:59 2004; andy

Packaged: Mon Sep 13 19:00:01 2004; andy

Packaged: Thu Nov 17 12:55:40 2005; andy

Packaged: Thu Apr  6 18:00:56 2006; andy

Packaged: Tue Nov 27 10:41:36 2007; liawand

Description: Local regression, likelihood and density estimation.

Title: Local Regression, Likelihood and Density Estimation
Authors@R: c(person("Catherine", "Loader", role = "aut"),
person("Lucent Technologies", role = "cph"),
Description: Local regression, likelihood and density estimation methods as described in the 1999 book by Loader.

Title: Test of stationarity and localized autocovariance
Description: Provides test of second-order stationarity for time
series. Provides localized autocovariance, with confidence
intervals, for locally stationary (nonstationary) time series.

Title: Test of Stationarity and Localized Autocovariance
series (for dyadic and arbitrary-n length data). Provides
localized autocovariance, with confidence intervals,
for locally stationary (nonstationary) time series.

See Nason, G P (2013) "A test for second-order stationarity and
approximate confidence intervals for localized autocovariance
for locally stationary time series." Journal of the Royal Statistical

Package: locpol
Version: 0.2-0
Date: 2007-10-01
Title: Kernel local polinomial regression.
Author: Jorge Luis Ojeda Cabrera, <jojeda@unizar.es>
Description: Computes local polynomial estimators.
Depends: R (>= 2.5.0)
Maintainer: Jorge Luis Ojeda Cabrera <jojeda@unizar.es>
License: GPL
Packaged: Tue Dec 18 11:37:42 2007; jorge

Title: Kernel local polynomial regression

Title: Kernel Local Polynomial Regression
Description: Computes local polynomial estimators for
the regression and also density. It comprises several
different utilities to handle kernel estimators.