[1] Stein, M. L. (1984). System parameters governed by jump processes: a model for removal of air polluants.
*Advances in Applied Probability*, **16**, 603-617.

[2] Stein, M. L. (1986). An efficient method of sampling for statistical circuit design.* IEEE
Transactions on Computer-Aided Design*, **CAD-5**, 23-29.

[3] Stein, M. L. (1986). A modification of minimum norm quadratic estimation of a generalized covariance function
for use with large data sets. *Mathematical Geology*, **18**, 625-633.

[4] Stein, M. L. (1986). A simple model for spatial-temporal processes.
*Water Resources Research*, **22**, 2107-2110.

[5] Stein, M. L. (1987). Large sample properties of simulations using Latin hypercube sampling.
*Technometrics*, **29**, 143-151. Correction, 32, 367.

[6] Stein, M. L. (1987). Gaussian approximations to conditional distributions for multigaussian processes.
*Mathematical Geology*, **19**, 387-405.

[7] Stein, M. L. (1987). Minimum norm quadratic estimation of spatial variograms.
*Journal of the American Statistical Association*, **82**, 765-772.

[8] Stein, M. L. (1988). Asymptotically efficient prediction of a random field with a misspecified covariance function.
*Annals of Statistics*, **16**, 55-63.

[9] Stein, M. L. (1988). An application of the theory of equivalence of Gaussian measures to a prediction problem.
*IEEE Transactions on Information Theory*, **34**, 580-582.

[10] Stein, M. L. and Handcock, M. S. (1989). Some asymptotic properties of kriging when the covariance function is misspecified. *Mathematical Geology*, **21**, 171-190.

[11] Stein, M. L. (1989). The loss of efficiency in kriging prediction
caused by misspecifications of the covariance structure.
*Geostatistics*, vol. 1, ed. M. Armstrong. Kluwer, Dordrecht, 273-282.

[12] Stein, M. L. (1989). Asymptotic distributions of minimum norm quadratic estimators of the covariance function
of a Gaussian random field. *Annals of Statistics*, **17**, 980-1000.

[13] Stein, M. L. (1990). Uniform asymptotic optimality of linear predictions of a random field using an
incorrect second-order structure. *Annals of Statistics*, **18**, 850-872.

[14] Stein, M. L. (1990). Bounds on the efficiency of linear predictions using an incorrect covariance function.
*Annals of Statistics*, **18**, 1116-1138.

[15] Stein, M. L. (1990). A comparison of generalized cross validation and modified maximum likelihood
for estimating the parameters of a stochastic process. *Annals of Statistics*, **18**,
1139-1157.

[16] Stein, M. L. (1991). A kernel approximation to the kriging predictor
of a spatial process. *Annals of the Institute of Statistical Mathematics*, ** 43**, 61-75.

[17] Stein, M. L. (1991). A new class of estimators for the reduced second moment measure of point processes.
*Biometrika*, **78**, 281-286.

[18] Niu, X. and Stein, M. L. (1992). Space-time ARMA models for satellite ozone data.
*Computing Science and Statistics*, eds. C. Page and R. LePage.
Springer-Verlag, New York, 225-234.

[19] Stein, M. L. (1992). Prediction and inference for truncated spatial
data. *Journal of Computational and Graphical Statistics*, **1**, 91-110.

[20] Styer, P. E. and Stein, M. L. (1992). Acid deposition models for detecting the effect of
changes in emissions: an exploratory investigation utilizing meteorological variables.
*Atmospheric Environment*, **26A**, 3019-3028.

[21] Niu, X., Frederick, J. E., Stein, M. L. and Tiao, G. C. (1992). Trends in column ozone based on TOMS
data: Dependence on month, latitude and longitude. *Journal of Geophysical Research Atmospheres*,
**97**, D13, 14, 661-14,669.

[22] Stein, M. L. (1992). Estimating the effect of emissions strategies on wet deposition of sulfates.
*Environmetrics*, **3**, 235-259.

[23] Zhang, B. and Stein, M. L. (1993). Kernel approximations for universal kriging predictors.
*Journal of Multivariate Analysis*, **44**, 286-313.

[24] Handcock, M. S. and Stein, M. L. (1993). A Bayesian analysis of
kriging. *Technometrics*, **35**, 403-410.

[25] Stein, M. L. (1993). Spline smoothing with an estimated order parameter. *Annals of Statistics*,
** 21**, 1522-1544.

[26] Stein, M. L., Shen, X. and Styer, P. (1993). Applications of a simple regression model to acid rain data.
*Canadian Journal of Statistics*, **21**, 331-346.

[27] Stein, M. L. (1993). Asymptotically optimal estimation for the reduced second moment measure of
point processes. *Biometrika*, **78**, 281-286.

[28] Stein, M. L. (1993). Asymptotic properties of center systematic sampling for predicting integrals of spatial
processes. *Annals of Applied Probability*, **3**, 874-880.

[29] Stein, M. L. (1993). A simple condition for asymptotic optimality of linear predictions of random fields.
*Statistics and Probability Letters*, **17**, 399-404.

[30] Stein, M. L. (1995). An approach to asymptotic inference for spatial point processes. *Statistica
Sinica*, **5**, 221-234.

[31] Stein, M. L. (1995). Predicting integrals of stochastic processes. *Annals of Applied Probability*,
**5**, 158-170.

[32] Stein, M. L. (1995). Fixed domain asymptotics for spatial periodograms. *Journal of the American
Statistical Association*, **90**, 1277-1288.

[33] Stein, M. L. (1995). Predicting integrals of random fields using observations on a lattice.
*Annals of Statistics,* **23**, 1975-1990.

[34] Stein, M. L. (1995). Locally lattice sampling designs for isotropic random fields.
*Annals of Statistics*, **23**, 1991-2012.

[35] Floresroux, E. M. and Stein, M. L. (1996). A new method of edge
correction for estimating the nearest neighbor distribution. *Journal of Statistical Planning and Inference*,
**50**, 353-371.

[36] Stein, M. L. (1997). Efficiency of linear predictors for periodic processes using an incorrect covariance
function. *Journal of Statistical Planning Inference*, **58**, 321-331.

[37] Fang, D. and Stein, M. L. (1998). Some statistical methods for analyzing the TOMS data. *Journal
of Geophysical Research*, **103**, 26,165-26,182.

[38] Stein, M. L. (1999). Predicting random fields with increasingly dense observations. * Annals of Applied
Probability*, **9**, 242-273.

[39] Quashnock, J. M. and Stein, M. L. (1999). A new measure of the
clustering of QSO heavy-element absorption-line
systems. *Astrophysical Journal*, **515**, 506-511

[40] Stein, M. L. (1999). Inference for point processes based on many short realizations. In
*Proceedings of the 31st Symposium on the Interface: Models, Predictions, and Computing*, eds. K. Berk and M.
Pourahmadi. Interface Foundation of North America, Fairfax, VA, 352-360.

[41] Stein, M. L., Quashnock, J. M. and Loh, J. M. (2000). Estimating the K function of a point process with an
application to cosmology. *Annals of Statistics*, **28**, 1503-1532.

[42] Stein, M. L. (2001). Local stationarity and simulation of self-affine intrinsic random functions.
*IEEE Transactions on Information Theory*, **47**, 1385-1390.

[43] Loh, J. M., Quashnock, J. M. and Stein, M. L. (2001). A measurement of the threedimensional clustering of
C IV absorption-line systems on scales of 5 to 300 h^{-1} Mpc. *Astrophysical Journal*, **560**, 606-616.

[44] Stein, M. L. (2002). The screening effect in kriging. *Annals of Statistics*, **30**, 298-323.

[45] Stein, M. L (2002). Fast and exact simulation of fractional Brownian surfaces. *Journal
of Computational and Graphical Statistics*, **11**, 587-599.

[46] Choi, D., Tiao, G. C. and Stein, M. L. (2002). A statistical model for latitudinal correlations of
satellite data. *Journal of Geophysical Research*, **107**, art. no. 4295.

[47] Lesht, B. M., Stroud, J. R., McCormick, M. J., Fahnensteil, G. L., Stein, M. L., Welty, L. J.
and Leshkevich, G. A. (2002). An event-driven phytoplankton bloom in southern Lake Michigan observed by satellite.
*Geophysical Research Letters*, **29**, 10. 1029/2001GL013533.

[48] Zhu, Z. and Stein, M. L.(2002). Parameter estimation for fractional
Brownian surfaces. *Statistica Sinica*, **12**, 863-883.

[49] Loh, J. M., Stein, M. L. and Quashnock, J. M. (2003). Estimating the large-scale structure of the
universe using QSO carbon IV absorbers. *Journal of the American Statistical Association*,
**98,** 522-532.

[50] Stein, M. L. (2004). Equivalence of Gaussian measures for some nonstationary random fields.
*Journal of Statistical Planning and Inference*, **123**, 1-11.

[51] Welty, L. J. and Stein, M. L. (2004). Modeling phytoplankton: Covariance and variogram model specification
for phytoplankton levels in Lake Michigan. In *geoENV IV, Geostatistics for Environmental Applications*,
eds. X. Sanchez-Vila, J. Carrera and J. J. Gomez-Hernandez. Kluwer, Dordrecht, 163-173.

[52] Loh, J. M. and Stein, M. L. (2004). Bootstrapping a spatial point process. *Statistica Sinica*,
**14,** 69-101.

[53] Stein, M. L., Chi, Z. and Welty, L. J. (2004). Approximating likelihoods for large spatial datasets.
* Journal of the Royal Statistical Society, Series B*, **66**, 275-296.

[54] Jun, M. and Stein, M. L. (2004). Statistical comparison of observed
and CMAQ modeled daily sulfate levels. *Atmospheric Environment*, **38**, 4427-4436.

[55] Guillas, S., Stein, M. L., Wuebbles, D. J. and Xia, J. (2004). A statistical evaluation of total
ozone trends using a chemical-transport model. *Journal of Geophysical Research*, **109**, D22303, doi:
10.1029/2004JD005049.

[56] Stein, M. L. (2005). Space-time covariance functions. *Journal of the American Statistical
Association*, **100**, 310-321.

[57] Stein, M. L. (2005). Statistical methods for regular monitoring data. *Journal of the Royal
Statistical Society, Series B*, **67**, 667-687.

[58] Im, H., Stein, M. L. and Kotomarthi, V. R. (2005). A new approach to scenario analysis using simplified
chemical transport *n*models. *Journal of Geophysical Research*, **110**, D24205, doi: 10.1029/2005JD006417.

[59] Zhu, Z. and Stein, M. L. (2005). Spatial sampling design for parameter
estimation of the covariance function. *Journal of Statistical Planning and
Inference*, **134**, 583-603.

[60] Zhu, Z. and Stein, M. L. (2006). Spatial sampling design for prediction with estimated parameters.
*Journal of Agricultural, Biological and Environmental Statistics*, **11**, 24-49.

[61] Shao, X. and Stein, M. L. (2006). Statistical conditional simulation of a multiresolution numerical
air quality model. *Journal of Geophysical Research, Atmospheres*. Vol. 111, D15211, doi:10.1029/2005JD007037.

[62] Vrac, M., Hayhoe, K. and Stein, M. L. (2006). Identification and inter-model comparison of seasonal
circulation patterns over North America. *International Journal of Climatology*, DOI: 10.1002/joc.1422.

[63] Stein, M. L. (2007). Seasonal variations in the spatial-temporal dependence of total column ozone.
*Environmetrics*, **18**, 71-86.

[64] Shao, X., Stein, M. L. and Ching, J. (2007). Statistical comparisons of methods for interpolating the output
of a numerical air quality model. *Journal of Statistical Planning and Inference*, **137**, 2277-2293.

[65] Jun, M. and Stein, M. L. (2007). An approach to producing space-time covariance functions on spheres.
*Technometrics*, **49**, 468-479.

[66] Im., H. K., Stein, M. L. and Zhu, Z. (2007). Semiparametric estimation of spectral density with
irregular observations. *Journal of the American Statistical Association*, **102**, 726-735.

[67] Stein, M. L. (2007). Spatial variation of total column ozone on a
global scale. *Annals of Applied Statistics*, **I**, 191-210.

[68] Vrac, M., Stein, M. L., Hayhoe, K. (2007). Statistical downscaling of precipitation through a nonhomogeneous
stochastic weather typing approach. *Journal of Climate Research,* **34**, 169-184.

[69] Zhang, Z., Beletsky, D., Schwab, D. J. and Stein, M. L. (2007). Assimilation of current measurements into
a circulation model of Lake Michigan. *Water Resources Research*,
**43**, Art. No. W11407.

[70] Vrac, M., Stein, M. L., Hayhoe, K. and Liang, X. Z. (2007). A general method for validating statistical
downscaling methods under future climate change. *Geophysical Research Letters*, **34**, Art. No. L18701.

[71] Stein, M. L. (2007). A modeling approach for large spatial datasets. *Journal of the Korean Statistical
Society*, 37/1, pp. 3-10, doi:10.1016/j.jkss.2007.09.001.

[72] Jun, M. and Stein, M. L. (2008). Nonstationary covariance models for global data. *Annals of Applied
Statistics*, **2,** 1271-1289.

[73] Anderes, E. B. and Stein, M. L.(2008). Estimating deformations of isotropic Gaussian random fields on the
plane. *Annals of Statistics*, **36**, 719-741.

[74] Loh, J. M. and Stein, M. L. (2008). Spatial bootstrap with increasing observations in a fixed domain.
*Statistica Sinica*, **18,** 667-688.

[75] Lim, C. and Stein, M. L. (2008). Asymptotic properties of spatial cross-periodograms using fixed-domain asymptotics.
*Journal of Multivariate Analysis*, **99**, 1962-1984.

[76] Stroud, J., Lesht, B., Schwab, D., Beletsky, D. and Stein, M. L. (2009). Assiimilation of satellite
images into a sediment transport model of Lake Michigan.*Water Resources Research*, **45**, W02419.

[77] Stein, M. L. (2009). Spatial interpolation of high frequency monitoring data. *Annals of Applied Statistics*,
**3**, 272-291.

[78] Lim, C., Stein, M. L., Ching, J. and Tang, R. (2010). Statistical properties of differences between low and
high resolution CMAQ runs with matched initial and boundary conditions. *Environmental Modeling & Software*, **25**, 158-169.

[79] Stroud, J. R., Stein, M. L., Lesht, B. M., Schwab, D. J. and Beletsky,
D. (2010).
An ensemble Kalman filter and smoother for satellite data assimilation. *Journal of the American Statistical
Association*, **105**, 978-990.

[80] Ma, L., Stein, M. L., Wang, M., Shelton, A. O., Pfister, C. A., and
Wilder, K. J. (2011).
A method for unbiased estimation of population abundance along curvy margins.
*Environmetrics*, **22**, 330-339, doi:10.1002/env.1053.

[81] Anderes, E. and Stein, M. L.
(2011).
Local likelihood estimation for nonstationary random fields.
*Journal of Multivariate Analysis*, **102**, 506-520.

[82] Stein, M. L.
(2011).
When does the screening effect hold?
*Annals of Statistics*, **39**, 2795-2819.

[83] Hitczenko, M. and Stein, M. L.
(2012).
Some theory for anisotropic processes on the sphere.
*Statistical Methodology*, **9**, 211-227.

[84] Stein, M. L., Chen, J. and Anitescu, M. (2012).
Difference filter preconditioning for large covariance matrices.
*SIAM Journal on Matrix Analysis and Applications*, **33**, 52-72.

[85] Stein, M. L.
(2012).
Simulation of Gaussian random fields with one derivative.
*Journal of Computational and Graphical Statistics*, **21**, 155-173.

[86] Porcu, E. and Stein, M. L. (2012). On some local, global and
regularity behaviour of some classes of covariance functions.
In: Porcu E., Montero J., Schlather M. (eds), *Advances and Challenges in
Space-time Modelling of Natural Events. Lecture Notes in Statistics, vol
207*. Springer, Berlin.

[87] Stein, M. L., Chen, J. and Anitescu, M.
(2013).
Stochastic approximation of score functions for Gaussian processes.
*Annals of Applied Statistics*, **7**,
1162-1191.

[88] Castruccio, S. and Stein, M. L.
(2013).
Global space-time models for climate ensembles.
*Annals of Applied Statistics*, **7**, 1593-1611.

[89] Guinness, J. and Stein, M. L. (2013).
Interpolation of nonstationary high frequency spatial-temporal temperature
data. *Annals of Applied Statistics*, **7**,
1684-1708.

[90] Guinness, J. and Stein, M. L. (2013).
Transformation to approximate independence for locally stationary Gaussian
processes.
*Journal of Time Series Analysis*, **34**, 574-590.

[91] Stein, M. L. (2013). Statistical properties of covariance tapers.
*Journal of Computational and Graphical Statistics*, **22**, 866-885.

[92] Chang, X. and Stein, M. L. (2013).
Decorrelation property of discrete wavelet transform under fixed-domain
asymptotics.
*IEEE Transactions on Information Theory*, **59**, 8001-8013.

[93] Stein, M. L. (2013).
On a class of space-time intrinsic random functions.
*Bernoulli*, **19**, 387-408.

[94] Stein, M. L. (2014).
Limitations on low rank approximations for covariance matrices of
spatial data.
*Spatial Statistics*, **8**, 1-19.

[95] Castruccio, S., McInerney, D. J.,
Stein, M. L., Crouch, F., Jacob, R. L. and Moyer, E. J.
(2014).
Statistical emulation of climate model projections based
on precomputed GCM runs.
*Journal of Climate*, **27**, 1829-1844.

[96] Poppick, A. and Stein, M. L. (2014). Using covariates to model dependence
innonstationary, high-frequencymeteorological processes.
*Environmetrics*, **25**, 293-305.

[97] Chang, X. and Stein, M. L. (2014).
Wavelet methods in interpolation of high-frequency spatial-temporal pressure.
*Spatial Statistics*, **8**, 52-68.

[98] Leeds, W. B., Moyer, E. J., Stein, M. L.
(2015).
Simulation of future climate under changing temporal covariance structures.
*Advances in Statistical Climatology, Meteorology and Oceanography*,
**1**, 1-14.

[99] Stein, M. L. (2015). When does the screening effect not hold?
*Spatial Statistics*, **11**, 65-80.

[100] Horrell, M. T. and Stein, M. L. (2015).
A covariance parameter estimation method
for polar-orbiting satellite data. *Statistica Sinica*, **25**,
41-59.

[101] Wang, J., Swati, Stein, M. L. and Kotamarthi, V. R. (2015).
Model performance in spatiotemporal patterns of precipitation: New
methods for identifying value added by a regional climate model.
*Journal of Geophysical Research Atmospheres*, **120**,
1239-1259.

[102] Sun, Y. and Stein, M. L. (2015). A stochastic space-time model for
intermittent precipitation occurrences. *Annals of Applied Statistics*,
**9**, 2110-2132.

[103] Sun, Y. and Stein, M. L. (2016). Statistically and computationally
efficient estimating equations for large spatial datasets. *Journal of
Computational and Graphical Statistics,* **25**, 187-208.

[104] Wang, J., Han, Y., Stein, M. L., Kotamarthi, V. R., Huang, W. K. (2016).
Evaluation of dynamically downscaled extreme temperature using a
spatially-aggregated generalized
extreme value (GEV) model. *Climate Dynamics*,
doi:10.1007/s00382-016-3000-3.

[105] Poppick, A., McInerney, D. J., Moyer, E. J., Stein, M. L. (2016).
Temperatures in transient climates: improved methods for simulations with
evolving temporal covariances. *Annals of Applied Statistics*,
**10**, 477-505.

[106] Huang, W. K., Stein, M. L., McInerney, D. J., Sun, S.,
Moyer, E. J. (2016).
Estimating changes in temperature extremes from millennial-scale climate
simulations using generalized extreme value (GEV) distributions.
*Advances in Statistical Climatology, Meteorology and Oceanograpy*,
**2**, 79-103.

[107] Bao, J., McInerney, D. J. and Stein, M. L. (2016). A spatial-dependent model
for climate emulation. *Environmetrics*, **27**, 396-408.
[108] Chang, W., Stein, M. L., Wang, J., Kotamarthi, V. R. and Moyer, E. J. (2016).
Changes in spatio-temporal precipitation patterns in changing
climate conditions. *Journal of Climate*, **29**, 8355-8376.
[109]
Anitescu, M., Chen, J. and Stein, M. L. (2017). An inversion-free estimating
equations approach for Gaussian process models. *Journal of
Computational and Graphical Statistics*, **26**, 98-107.
[110]
Stein, M. L. (2017). Should annual maximum temperatures follow a generalized
extreme value distribution?
*Biometrika*, **104**, 1-16.
[111]
Xu, W. and Stein, M. L. (2017). Maximum likelihood estimation for a smooth
Gaussian random field model.
*SIAM/ASA Journal on Uncertainty Quantification*, **5**, 138-175.
[112]
Poppick, A., Moyer, E. J. and Stein, M. L. (2017). Estimating trends in the
global mean temperature record.
*Advances in Statistical Climatology, Meteorology and Oceanography*,
**3**, 33-53.
[113]
Stroud, J. R., Stein, M. L. and Lysen, S. (2017). Bayesian and maximum
likelihood estimation for Gaussian processes on an incomplete lattice.
*Journal of Computational and Graphical Statistics*, **26**,
108-120.
[114]
Horrell, M. T. and Stein, M. L. (2017). Half-spectral space-time covariance
models. *Spatial Statistics*, **19**, 90-100.
[115]
Haugen, M. A., Stein, M. L. Moyer, E. J. Moyer and Sriver, R. L. (2018).
Estimating changes in temperature distributions in a large ensemble of climate
simulations using quantile regression. *Journal of Climate*,
**31**, 8573-8588.
[116]
Baugh, S. and Stein, M. L. (2018).
Computationally efficient spatial modeling using recursive skeletonization
factorizations. *Spatial Statistics*, **27**, 18-30.
[117]
Kuusela, M. and Stein, M. L. (2018).
Locally stationary spatio-temporal interpolation of Argo profiling float data.
*Proceedings of the Royal Sociey A*, **474**, 20180400.
[118]
Xu, W., Stein, M. L. and Wisher, I. (2019).
Modeling and predicting chaotic circuit data. *Journal of Uncertainty
Quantification*, **7**, 31-52.
[119]
Haugen, M. A., Stein, M. L., Sriver, R. L. and Moyer, E. J. (2019).
Future climate emulations using quantile regressions on large ensembles.
*Advances in Statistical Climatology, Meteorology and Oceanography*,
**5**, 37-55.
[120]
Geoga, C. J., Anitescu, M. and Stein, M. L. (2020).
Scalable Gaussian process computations using hierarchical matrices.
*Journal of Computational and Graphical Statistics*,
**29** 227-237.
[121]
Stein, M. L. (2020). Some statistical issues in climate science.
*Statistical Science*, **35**, 31-41.
[122]
Stein, M. L. (2021). Parametric models for distributions when interest
is in extremes with an application to daily temperature. *Extremes*,
**24**, 293-323.
https://doi.org/10.1007/s10687-020-00378-z.
[123]
Stein, M. L. (2020).
A parametric model for distributions with flexible behavior in both tails.
*Environmetrics*, 2020;e2658. https://doi.org/10.1002/env.2658
[124]
Yuan, J., Stein, M. L. and Kopp, R. E. (2020).
The evolving distribution of relative humidity conditional upon daily maximum
temperature in a warming climate.
*Journal of Geophysical Research: Atmospheres*, **125**,
e2019JD032100. https://doi.org/10.1029/2019JD032100
[125]
Geoga, C. J., Anitescu, M. and Stein, M. L. (2021). Flexible nonstationary
spatiotemporal modeling of high-frequency monitoring data.
*Environmetrics*, 2021;e2670. https://doi.org/10.1002/env.2670
**Discussions and reviews:**

[1] Stein, M. L. (1989). Discussion of “Space-time modelling with long-memory dependence: assessing Irelands
wind power resource,” by J. Haslett and A. Raftery. *Applied Statistics*, **38**, 39.

[2] Stein, M. L. (1989). Review of Statistical Analysis of Spherical Data by N. I. Fisher, T. Lewis, and
B. J. J. Embleton. *Technometrics*, **31**, 393-394.

[3] Stein, M. L. (1990). Discussion of “Design and Analysis of Computer Experiments,” by
J. Sacks, W. J. Welch, T. J., and H. P. Wynn. *Statistical Science*, **4**, 432-433.

[4] Stein, M. L. (1990). Review of Estimating and Choosing, by G. Matheron. *Technometrics*,
**32**, 358-359.

[5] Stein, M. L. (1991). Review of The Analysis of Directional Time Series: Applications to Wind Speed
and Direction, by J. Breckling. *Technometrics*, **33**, 485-486.

[6] Stein, M. L. and Fang, D. (1997). Discussion of “Ozone exposure and population density in Harris County, Texas,” by R. J. Carroll, et al. *Journal of the American Statistical Association*,
**92**, 408-411.

[7] Stein, M. L. (1998). Discussion of “Model-based geostatistics,” by P.J. Diggle, J.A. Tawn and
R.A. Moyeed. *Applied Statistics*, ** 47**, 341-342.

[8] Stein, M. L. (1998). Discussion of “The kriged Kalman filter,” by K. V. Mardia, et al. *Test,* **7**, 272-276.

[9] Stein, M. L. (1999). Discussion of “Prediction of spatial cummulative distribution functions using
subsampling,” by S. N. Lahiri, et al. *Journal of the American Statistical Association*, **94**, 106-107.

[10] Stein, M. L. (2000). Review of Geostatistics: Modeling Spatial Uncertainty, by J.-P. Chilès
and P. Delfiner. *Journal of the American Statistical Association*, **95**, 335-337.

[11] Fuentes, M., Guttorp, P. and Stein, M. L. (2008). Special section on statistics in the atmospheric sciences.
*Annals of Applied Statistics*, **2**, 1143-1147.

[12] Loredo, T. J., Rice, J. and Stein, M. L. (2009). Introduction to papers on astrostatistics. *Annals of Applied Statistics*, **3**, 1-5.

[13] Stein, M. L. (2010). Discussion of “Geostatistical inference
under preferential sampling,” by P.J. Diggle, R. Menezes and
T. Su. *Applied Statistics*, ** 59**, 223.

[14] Stein, M. L. (2011). Editorial. *Annals of Applied Statistics*, **5**,
1-4.

[15]
Katz, R. W., Craigmile, P. F.,Guttorp, P., Haran, M.,
Sansó, B. and Stein, M. L. (2013).
Uncertainty analysis in climate change assessments.
*Nature Climate Change*, **3**, 769-771.

[16]
Stein, M. L. and Hung, Y. (2019). Comment on ``Probabilistic integration: A
role in statistical computation?'' by F.-X. Briol, et al. *Statistical
Science*, **34**, 34--37.