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BIO (text) CV Everything: (html) (pdf) (LaTeX) NSF style (but topical): (pdf) (LaTeX) One pager: (pdf) (LaTeX)
Material for Workshop on Environmental Analytics,
CU  Boulder, June, 2014
Material for APPM course, CU  Boulder, June, 2014
Joint NCAR U Wyoming short course, Boulder, June,
2013
Ten Lectures on Statistics and Climate
CBMS Lecture Series, University of Washington,
Seattle, August 2012
Short course on Statistics and Regional
Climate
Institute of Mathematical Sciences, National
University of Singapore, Feb 28  March 4 2011
Useful datasets and source for interpreting the
NARCCAP model output..
Daily Surface Ozone Eastern US 19951999
An example of a nonstationary spatial process and
spatial extremes .
A case study dataset on Colorado
climate:

Regional climate model and observed precipitation
data for the Colorado Front Range. 
R packages

LatticeKrig is a
spatial method for large data sets that builds on compactly supported basis
functions, Markov random fields and sparse matrix methods. Downloading LatticeKrig: ¥
Beta version LatticeKrig_3.3.tar.gz
July112014. Depends on fields and spam packages. fields (home page) is a
collection of programs based in R for curve and function fitting with an
emphasis on spatial data and flexible covariance functions for Kriging. Downloading Fields: ¥ Beta
version  fields_7.1.2.tar.gz
Septemebr 152014. ¥ Binaries
and source supplied as a Software package by the Comprehensive
R Archive Network (CRAN) (This may be an older but perhaps more
stable version.) Short course CD A directory with the
lectures, source code, R binaries and R packages used in the ENAR short
course, MAR 2009. spam is a collection of functions based in R/Fortran for
sparse matrix algebra. Written by Reinhard Furrer with the attention to
detail that have made the Swiss famous! The fields pacakage uses these
functions for spatial analysis of large datasets. Current CRAN version: Version
0.23 SEP2010. 

Major fields functions:
Tps:
Thin Plate spline regression
Krig: Spatial process
estimate (Kriging)
This function allows you to supply a covariance
function as R code, uses sparse matrix methods from the spam package and can
handle large data sets.
mKrig (micro Krig ) and fastTps
Fast spatial prediction that can take advantage of compactly supported
covariance functions and handle big data sets
cover.design: Finds
a space filling design
as.image, image.plot, quilt.plot,
crop.image, average.image, designer.colors: Some useful functions for
working with image data on 2d grids and color scales
sreg, qsreg
: 1d smoothing splines and 1d quantile splines
There are also generic functions that support these
methods such as:
plot diagnostic plots of fit
summary
statistical summary of fit
surface graphical display of
fitted surface
predict, predict.se evaluation fit and
prediction error at arbitrary points
nnreg
Neural Networks Package. Estimates a function using
a single hidden layer neural network by nonlinear least squares. The fitting
algorithm is both robust and accurate. Has supporting functions for
diagnostics, GCV and graphing.
Doug Nychka (contact), Stephen Ellner and Barbara
Bailey nnreg_1.1.tar.gz
(59K)
lenns
Lyapunov Exponents fit by Neural Networks
Fits nonlinear autoregressive maps to multivariate
time series data and estimates global and local Lyapunov Exponents. Doug Nychka
(contact), Stephen Ellner and Barbara Bailey lenns_1.0.tar.gz
(25K)