Charles Kooperberg - Software
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clk@fredhutch.org
See also Mike LeBlanc's software page for software related to some joint projects.
Genetic association studies
Code for fitting an ultra-sparse variational Bayes spike regression model, with applications to
Genome-wide association studies (vBsr)
is here. WARNING: Code is in an early release form (version 0.0.1), and details of the model are forthcoming. Email questions to Ben Logsdon (blogsdon@u.washington.edu).
Code for approximate power calculations for identification of gene x gene and gene x environment interactions
in genomewide association studies using a two-stage analysis. Download the package powerGWASinteraction
from CRAN.
Code
for Adaptively Weighted Association Statistics is here. This is software written by Mike LeBlanc
mleblanc@fhcrc.org
that implements adaptive selection and weighting to potentially improve
the power of association testing of genetic factors with disease outcome.
Code
for SNP-Haplotype Adaptive Regression (SHARE)
to perform multi-locus analysis in order to account for LD patterns observed in human genome
developed by James Dai
jdai@scharp.org
is available in the package SHARE from CRAN.
Code
for
semiparametric estimation exploiting covariate independence in two-phase randomized trials
developed by James Dai
jdai@scharp.org
is available in the package TwoPhaseInd from CRAN.
Software that was supported in part by
ENDGAME (Enhancing Development of Genome-wide Association Methods) project
U01 CA 125489 Dissecting complex traits with diverse resources. Investigators
on this project were James Dai, Li Hsu, Charles Kooperberg, Michael LeBlanc,
Hua Tang, and Yingye Zheng.
Logic Regression
Logic Regression.
Logic Regression:
R libraries to fit logic regression models.
Microarrays
Improved background correction for spotted DNA microarrays: R code.
It is also implemented in Gordon Smyth's Limma package on bioconductor as the
function kooperberg.
Directed indices for exploring gene expression data:
code is here.
(Code written by Mike Leblanc mleblanc@fhcrc.org.)
Extreme regression
code is here.
(Code written by Mike Leblanc mleblanc@fhcrc.org.)
This method is
described in
M. LeBlanc, J. Moon, and C. Kooperberg. (2006)
Extreme regression.
Biostatistics, 7, 71-84.
Polynomial Splines
Libraries
Software for hare, heft, lspec, logspline, polyclass and polymars,
as well as the logspline version discussed in Stone et al (1997) are now
available as an R-package. You can download the package polspline from
CRAN.
(Version 1.0.11, 5/24/2005.)
Software for logspline
as well as the logspline version discussed in Stone et al (1997) are now
available as an R-package. You can download the package logspline from
CRAN.
(Version 2,9,2, 4/18/2005.) The latest version of logspline is always
part of the latest version of polspline .
A book about splines
Statistical Modeling with Spline Functions, an unfinished, incomplete, monograph.
Individual programs
I suggest downloading polspline
(see above),
it will give you all programs at once.
The programs on this page were last updated 03/10/2005. The programs
on statlib are no longer updated.
POLYCLASS.
Polyclass:
S functions to estimate conditional class probabilities
based on a discrete response variable and a number
of predictors.
tar.gz archive.
I suggest downloading polspline
(see above),
it will give you all programs at once.
POLYMARS.
Polymars:
A set of S functions for classification and (polychotomous) regression using adaptively selected polynomial splines for the model
building. (Written by Martin O'Connor under
my direction.)
I suggest downloading polspline
(see above),
it will give you all programs at once.
The POLYCLASS and POLYMARS programs are
described in
Polychotomous Regression. Charles
Kooperberg, Smarajit Bose and Charles J. Stone.
Journal of the American Statistical Association , 92, ,
117-127 (1997).
HARE.
Hazard Regression: S functions to estimate the conditional
log-hazard function based on
possibly censored data
and covariates and obtain corresponding densities, hazard rates,
probabilities, quantiles
and random samples. Includes proportional hazard model as special
case.
I suggest downloading polspline
(see above),
it will give you all programs at once.
HEFT.
Hazard Estimation with Flexible Tails:
S functions to estimate an unknown hazard function
based on possibly censored data
and obtain corresponding densities probabilities, quantiles and
random samples.
I suggest downloading polspline
(see above),
it will give you all programs at once.
The HARE and HEFT programs are
described in
Hazard Regression. Charles
Kooperberg, Charles J. Stone and Young K. Truong.
Journal of the American Statistical Association , 90, ,
78-94 (1995).
LOGSPLINE. There are two versions of this software.
OLDLOGSPLINE.
S functions to, fully automaticly, estimate an unknown density based
on possibly grouped or
censored data and obtain corresponding probabilities,
quantiles and random samples.
This function used to be known
as ``logspline'', it uses stepwise knot deletion from a larger number of initial knots.
I suggest downloading polspline
(see above),
it will give you all programs at once.
LOGSPLINE.
S functions to, fully automaticly, estimate an unknown density based
on possibly grouped or
censored data and obtain corresponding probabilities,
quantiles and random samples.
This function used to be known
as ``nlsd'', it uses stepwise addition and stepwise deletion of initial knots.
I suggest downloading polspline
(see above),
it will give you all programs at once.
LSPEC.
Logspline estimation of a
possibly mixed spectral distribution: S functions to estimate the
spectral density,
line spectrum and spectral distribution based on time series data.
I suggest downloading polspline
(see above),
it will give you all programs at once.