M. Stein

发表

STOCHASTIC APPROXIMATION OF SCORE FUNCTIONS FOR GAUSSIAN PROCESSES

M. Anitescu, M. Stein, Jie Chen, 2013, 1312.2687.

A kernel approximation to the kriging predictor of a spatial process

M. Stein, 1991 .

A Bayesian analysis of kriging

M. Stein, M. Handcock, 1993 .

Estimating deformations of isotropic Gaussian random fields on the plane

M. Stein, E. Anderes, 2008, 0804.0723.

Large sample properties of simulations using latin hypercube sampling

M. Stein, 1987 .

Spatial sampling design for prediction with estimated parameters

M. Stein, Zhengyuan Zhu, Zhengyuan Zhu, 2006 .

Nonstationary spatial covariance functions

M. Stein, 2005 .

[Design and Analysis of Computer Experiments]: Comment

M. Stein, 1989 .

Model-based geostatistics. Discussion. Authors' reply

T. C. Haas, M. Kenward, S. Nadarajah, 1998 .

Predicting random fields with increasing dense observations

M. Stein, 1999 .

Interpolation of spatial data

Michael L. Stein, M. Stein, 1999 .

Statistical comparison of observed and CMAQ modeled daily sulfate levels

M. Stein, M. Jun, 2004 .

Estimating and choosing

M. Stein, 1989 .

Space–Time Covariance Functions

M. Stein, 2005 .

An Inversion-Free Estimating Equations Approach for Gaussian Process Models

M. Anitescu, M. Stein, Jie Chen, 2017 .

Statistical Interpolation of Spatial Data: Some Theory for Kriging

M. Stein, 1999 .

Limitations on low rank approximations for covariance matrices of spatial data

Michael L. Stein, M. Stein, 2014 .

Properties of spatial cross-periodograms using fixed-domain asymptotics

Chae Young Lim, Michael L. Stein, M. Stein, 2008 .

Fixed-Domain Asymptotics for Spatial Periodograms

Michael L. Stein, M. Stein, 1995 .

Estimating the $K$ function of a point process with an application to cosmology

Dept. of Physics, Michael L. Stein, M. Stein, 2000, physics/0006047.

Simulation of Gaussian Random Fields With One Derivative

M. Stein, 2012 .

Predicting With Estimated Parameters

M. Stein, 1999 .

The Analysis of Directional Time Series: Applications to Wind Speed and Direction

M. Stein, 1991 .

Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets

Ying Sun, M. Stein, 2016 .

Uncertainty analysis in climate change assessments

P. Guttorp, M. Stein, P. Craigmile, 2013 .

Assimilation of current measurements into a circulation model of Lake Michigan

M. Stein, D. Beletsky, D. Schwab, 2007 .

Assimilation of satellite images into a sediment transport model of Lake Michigan

Jonathan R. Stroud, M. Stein, D. Beletsky, 2009 .

An Ensemble Kalman Filter and Smoother for Satellite Data Assimilation

Jonathan R. Stroud, M. Stein, D. Beletsky, 2010 .

Nonstationary covariance models for global data

Mikyoung Jun, Michael L. Stein, M. Stein, 2008, 0901.3980.

A general method for validating statistical downscaling methods under future climate change

Katharine Hayhoe, Michael L. Stein, M. Stein, 2007 .

Spatial sampling design for parameter estimation of the covariance function

Zhengyuan Zhu, Michael L. Stein, M. Stein, 2005 .

Approximating likelihoods for large spatial data sets

Zhiyi Chi, Michael L. Stein, Zhiyi Chi, 2004 .

Association Modeling and Predicting Chaotic Circuit Data ∗ Wanting

M. Stein, I. Wisher, Xu, 2019 .

Minimum norm quadratic estimation of spatial variograms

Michael L. Stein, M. Stein, 1987 .

DIFFERENCE FILTER PRECONDITIONING FOR LARGE

M. Anitescu, M. Stein, Jie Chen, 2014 .

A modeling approach for large spatial datasets

Michael L. Stein, M. Stein, 2008 .

Trends in column ozone based on TOMS data: Dependence on month, latitude, and longitude

G. C. Tiao, M. Stein, J. Frederick, 1992 .

Statistical comparisons of methods for interpolating the output of a numerical air quality model

Michael L. Stein, Jason Ching, Xiaofeng Shao, 2007 .

Some statistical methods for analyzing the TOMS data

Michael L. Stein, M. Stein, Dongping Fang, 1998 .

Efficiency of linear predictors for periodic processes using an incorrect covariance function

Michael L. Stein, M. Stein, 1997 .

Book Reviews

David R. Anderson, Richard A. Levine, Engin A. Sungur, 2000 .

A new method of edge correction for estimating the nearest neighbor distribution

M. Stein, Ernesto M. Floresroux, 1996 .

On a class of space–time intrinsic random functions

M. Stein, 2013, 1303.4620.

Statistical methods for regular monitoring data

Michael L. Stein, M. Stein, 2005 .

Predicting Integrals of Stochastic Processes

M. Stein, 1995 .

Equivalence of Gaussian measures for some nonstationary random fields

Michael L. Stein, M. Stein, 2004 .

Statistical Properties of Covariance Tapers

Michael L. Stein, M. Stein, 2013 .

Some Statistical Issues in Climate Science

M. Stein, 2020 .

A New Measure of the Clustering of QSO Heavy-Element Absorption-Line Systems

M. Stein, J. Quashnock, 1998, astro-ph/9808238.

Asymptotically Efficient Prediction of a Random Field with a Misspecified Covariance Function

Michael L. Stein, M. Stein, 1988 .

Half-Spectral Space-Time Covariance Models

M. Stein, M. Horrell, 2015, 1505.01243.

Simulation of future climate under changing temporal covariance structures

M. Stein, E. Moyer, W. Leeds, 2015 .

Wavelet methods in interpolation of high-frequency spatial–temporal pressure

M. Stein, Xiaohui Chang, 2014 .

Predicting integrals of random fields using observations on a lattice

Michael L. Stein, M. Stein, 1995 .

Acid deposition models for detecting the effect of changes in emissions: an exploratory investigation utilizing meteorological variables

M. Stein, P. Styer, 1992 .

Book Reviews

M. Stein, B. Vidakovic, R. Zwick, 2000 .

LOCALLY LATTICE SAMPLING DESIGNS FOR ISOTROPIC

M. Stein, Random Fields, 1996 .

Using chemistry transport modeling in statistical analysis of stratospheric ozone trends from observations

M. Stein, D. Wuebbles, S. Guillas, 2004 .

STATISTICAL DOWNSCALING OF PRECIPITATION THROUGH A NONHOMOGENEOUS STOCHASTIC WEATHER TYPING APPROACH

M. Stein, M. Vrac, K. Hayhoe, 2007 .

A Measurement of the Three-dimensional Clustering of C IV Absorption-Line Systems on Scales of 5-1000 h–1 Mpc

M. Stein, J. Quashnock, J. Loh, 2001 .

Fitting Matérn smoothness parameters using automatic differentiation

Christopher J. Geoga, M. Stein, O. Marin, 2022, Statistics and Computing.

The Evolving Distribution of Relative Humidity Conditional Upon Daily Maximum Temperature in a Warming Climate

M. Stein, R. Kopp, Jiacan Yuan, 2019, Journal of Geophysical Research: Atmospheres.

A New Measure of the Clustering of QSO Heavy-Element Absorption-Line Systems

M. Stein, J. Quashnock, 1998, astro-ph/9808238.

Equivalence of Gaussian Measures and Prediction

M. Stein, 1999 .

Parametric models for distributions when interest is in extremes with an application to daily temperature

M. Stein, 2020, Extremes.

Asymptotically optimal estimation for the reduced second moment measure of point processes

M. Stein, 1993 .

On Some Local, Global and Regularity Behaviour of Some Classes of Covariance Functions

Emilio Porcu, Michael L. Stein, M. Stein, 2012 .

Changes in Spatiotemporal Precipitation Patterns in Changing Climate Conditions

Elisabeth J. Moyer, Won Chang, Michael L. Stein, 2016, 1601.01147.

Using covariates to model dependence in nonstationary, high‐frequency meteorological processes

Michael L. Stein, Andrew Poppick, M. Stein, 2014 .

The screening effect in Kriging

Michael L. Stein, M. Stein, 2002 .

Future climate emulations using quantile regressions on large ensembles

Ryan L. Sriver, Elisabeth J. Moyer, Matz A. Haugen, 2019, Advances in Statistical Climatology, Meteorology and Oceanography.

Estimating Changes in Temperature Distributions in a Large Ensemble of Climate Simulations Using Quantile Regression

Matz A. Haugen, M. Stein, E. Moyer, 2018, Journal of Climate.

Locally stationary spatio-temporal interpolation of Argo profiling float data

Mikael Kuusela, Michael L Stein, M. Stein, 2017, Proceedings of the Royal Society A.

Interpolation of nonstationary high frequency spatial–temporal temperature data

Joseph Guinness, Michael L. Stein, M. Stein, 2013, 1311.7472.

Global space–time models for climate ensembles

Michael L. Stein, Stefano Castruccio, M. Stein, 2013, 1311.7319.

Bayesian and Maximum Likelihood Estimation for Gaussian Processes on an Incomplete Lattice

Michael L. Stein, Jonathan R. Stroud, Shaun Lysen, 2014, 1402.4281.

Locally lattice sampling designs for isotropic random fields

Michael L. Stein, M. Stein, 1995 .

An Approach to Producing Space–Time Covariance Functions on Spheres

Mikyoung Jun, Michael L. Stein, M. Stein, 2007, Technometrics.

Estimating the Large-Scale Structure of the Universe Using Quasi-Stellar Object Carbon IV Absorbers

M. Stein, J. Quashnock, J. Loh, 2003 .

Maximum Likelihood Estimation for a Smooth Gaussian Random Field Model

Michael L. Stein, Wanting Xu, M. Stein, 2017, SIAM/ASA J. Uncertain. Quantification.

Estimating Large-Scale Structure From QSO Absorbers: Using Across-Line Information

M. Stein, J. Quashnock, J. Loh, 2003 .

Difference Filter Preconditioning for Large Covariance Matrices

Mihai Anitescu, Jie Chen, Michael L. Stein, 2012, SIAM J. Matrix Anal. Appl..

Prediction and Inference for Truncated Spatial Data

Michael L. Stein, M. Stein, 1992 .

Statistical Analysis of Spherical Data

M. Stein, 1989 .

A method for unbiased estimation of population abundance along curvy margins

M. Stein, Kenneth Wilder, Mei Wang, 2011 .

Semiparametric Estimation of Spectral Density With Irregular Observations

Zhengyuan Zhu, Hae Kyung Im, Michael L. Stein, 2007 .

A new approach to scenario analysis using simplified chemical transport models

M. Stein, H. Im, V. Kotamarthi, 2005 .

Neural networks for parameter estimation in intractable models

Johann Rudi, Julie Bessac, Amanda Lenzi, 2021, Comput. Stat. Data Anal..

PARAMETER ESTIMATION FOR FRACTIONAL BROWNIAN SURFACES

Zhengyuan Zhu, Michael L. Stein, M. Stein, 2003 .

A stochastic space-time model for intermittent precipitation occurrences

Michael L. Stein, Ying Sun, M. Stein, 2016, 1602.02902.

Spatial interpolation of high-frequency monitoring data

Michael L. Stein, M. Stein, 2009, 0906.1115.

Some asymptotic properties of kriging when the covariance function is misspecified

Mark S. Handcock, Michael L. Stein, M. Stein, 1989 .

When does the screening effect not hold

M. Stein, 2015 .

2010 RIETZ WHEN DOES THE SCREENING EFFECT HOLD?

M. Stein, Rietz Lecture, 2012 .

2010 Rietz lecture: When does the screening effect hold?

Michael L. Stein, M. Stein, 2011, 1203.1801.

The Loss of Efficiency in Kriging Prediction Caused by Misspecifications of the Covariance Structure

Michael L. Stein, M. Stein, 1989 .

Nonstationary seasonal model for daily mean temperature distribution bridging bulk and tails

Julie Bessac, Adam H. Monahan, Michael L. Stein, 2021, Weather and Climate Extremes.

A weighted composite log-likelihood approach to parametric estimation of the extreme quantiles of a distribution

M. Stein, 2023, Extremes.

Parametric models for distributions when interest is in extremes with an application to daily temperature

M. Stein, 2020 .

Estimating trends in the global mean temperature record

Elisabeth J. Moyer, Michael L. Stein, Andrew Poppick, 2016, 1607.03855.

Estimating changes in temperature extremes from millennial scale climate simulations using generalized extreme value (GEV) distributions

Elisabeth J. Moyer, Michael L. Stein, Whitney K. Huang, 2015, 1512.08775.

Ozone Exposure and Population Density in Harris County, Texas: Comment

Michael L. Stein, M. Stein, Dongping Fang, 1997 .

A note on the smoothness of densities

Michael L. Stein, M. Stein, 2022 .

Gaussian approximations to conditional distributions for multi-Gaussian processes

M. Stein, 1987 .

Statistical emulation of climate model projections based on precomputed GCM runs

Robert Jacob, Michael L. Stein, Stefano Castruccio, 2013 .

Climate Change Impacts at Department of Defense Installations

M. Stein, D. Wuebbles, K. Hayhoe, 2017 .

Model performance in spatiotemporal patterns of precipitation: New methods for identifying value added by a regional climate model

Michael L. Stein, Jiali Wang, V. Rao Kotamarthi, 2015 .

Should annual maximum temperatures follow a generalized extreme value distribution?

M. Stein, 2017 .

Statistical downscaling of precipitation through nonhomogeneous stochastic weather typing

Katharine Hayhoe, Michael L. Stein, M. Stein, 2007 .

Scalable Gaussian Process Computations Using Hierarchical Matrices

Mihai Anitescu, Michael L. Stein, Christopher J. Geoga, 2018, Journal of Computational and Graphical Statistics.

Linear-Cost Covariance Functions for Gaussian Random Fields

Jie Chen, Michael L. Stein, M. Stein, 2017, Journal of the American Statistical Association.

A Scalable Method to Exploit Screening in Gaussian Process Models with Noise

Christopher J. Geoga, M. Stein, 2022, 2208.06877.

Scalable computations for nonstationary Gaussian processes

Christopher J. Geoga, Paul G. Beckman, M. Anitescu, 2022, Statistics and Computing.

A simple condition for asymptotic optimality of linear predictions of random fields

Michael L. Stein, M. Stein, 1993 .

Uniform Asymptotic Optimality of Linear Predictions of a Random Field Using an Incorrect Second-Order Structure

Michael L. Stein, M. Stein, 1990 .

A simple model for spatial‐temporal processes

Michael L. Stein, M. Stein, 1986 .

Spline smoothing with an estimated order parameter

M. Stein, 1993 .

Preprint ANL/MCS-P1888-0511 DIFFERENCE FILTER PRECONDITIONING FOR LARGE COVARIANCE MATRICES

M. Anitescu, M. Stein, Jie Chen, 2011 .

Local likelihood estimation for nonstationary random fields

Michael L. Stein, Ethan B. Anderes, M. Stein, 2011, J. Multivar. Anal..

Local variogram models with negative inverse “range” parameters

M. Stein, 2022, Spatial Statistics.

Local stationarity and simulation of self-affine intrinsic random functions

Michael L. Stein, M. Stein, 2001, IEEE Trans. Inf. Theory.

Modeling Phytoplankton: Covariance and Variogram Model Specification for Phytoplankton Levels in Lake Michigan

M. Stein, L. Welty, 2004 .

Spatial variation of total column ozone on a global scale

Michael L. Stein, M. Stein, 2007, 0709.0394.

Fast and Exact Simulation of Fractional Brownian Surfaces

Michael L. Stein, M. Stein, 2002 .

Statistical properties of differences between low and high resolution CMAQ runs with matched initial and boundary conditions

Michael Stein, Chae Young Lim, Jason Ching, 2010, Environ. Model. Softw..

Evaluation of dynamically downscaled extreme temperature using a spatially-aggregated generalized extreme value (GEV) model

Whitney K. Huang, M. Stein, Yuefeng Han, 2016, Climate Dynamics.

Temperatures in transient climates: improved methods for simulations with evolving temporal covariances

M. Stein, E. Moyer, D. McInerney, 2015, 1507.00683.

Computationally efficient spatial modeling using recursive skeletonization factorizations

Michael L. Stein, Samuel Baugh, M. Stein, 2018, Spatial Statistics.

A COVARIANCE PARAMETER ESTIMATION METHOD FOR POLAR-ORBITING SATELLITE DATA

Michael Horrell, Michael L. Stein, M. Stein, 2014 .

Transformation to approximate independence for locally stationary Gaussian processes

Joseph Guinness, Michael Stein, M. Stein, 2013 .

Bounds on the Efficiency of Linear Predictions Using an Incorrect Covariance Function

Michael L. Stein, M. Stein, 1990 .

Locally stationary spatio-temporal interpolation of Argo profiling float data

M. Stein, Mikael Kuusela, 2017, Proceedings of the Royal Society A.

A Comparison of Generalized Cross Validation and Modified Maximum Likelihood for Estimating the Parameters of a Stochastic Process

Michael L. Stein, M. Stein, 1990 .

A Measurement of the Three-dimensional Clustering of C IV Absorption-Line Systems on Scales of 5-1000 h–1 Mpc

M. Stein, J. Quashnock, J. Loh, 2001 .

SPATIAL BOOTSTRAP WITH INCREASING OBSERVATIONS IN A FIXED DOMAIN

M. Stein, J. Loh, 2008 .

A statistical model for latitudinal correlations of satellite data

M. Stein, Dongseok Choi, G. Tiao, 2002 .

Global space–time models for climate ensembles

M. Stein, S. Castruccio, 2013, 1311.7319.

Prediction of Spatial Cumulative Distribution Functions Using Subsampling: Comment

M. Stein, 1999 .

Statistical Interpolation of Spatial Data: Some Theory for Kriging

M. Stein, 1999 .

System parameters governed by jump processes: a model for removal of air pollutants

M. Stein, 1984, Advances in Applied Probability.

Vecchia Likelihood Approximation for Accurate and Fast Inference in Intractable Spatial Extremes Models

M. Stein, P. Zhong, Raphael Huser, 2022, 2203.05626.

On Some Local, Global and Regularity Behaviour of Some Classes of Covariance Functions

M. Stein, E. Porcu, 2012 .