Flexible Gaussian Processes via Convolution

A hardy rose plant of the hybrid miniature class, having a vigorous growth habit, and having slightly better than average resistance to mildew, said plant producing, throughout the growing season, a profusion of well-formed buds and flowers, these latter being from about 1 inch to 11/4 inches in size and having from 22 to 28 petals plus 2 to 6 petaloids. The overall color effect of the flowers is rather uniformly coral and pink. The flowers are sterile, and do not generally set hips.

[1]  Ronald P. Barry,et al.  Blackbox Kriging: Spatial Prediction Without Specifying Variogram Models , 1996 .

[2]  Kamy Sepehrnoori,et al.  Partitioning Tracer Test for Detection, Estimation, and Remediation Performance Assessment of Subsurface Nonaqueous Phase Liquids , 1995 .

[3]  S. Frühwirth-Schnatter.  Data Augmentation and Dynamic Linear Models , 1994 .

[4]  D. Higdon,et al.  Exploring Space-Time Structure in Ozone Concentration Using a Dynamic Process Convolution Model , 2002 .

[5]  D. Higdon.  Space and Space-Time Modeling using Process Convolutions , 2002 .

[6]  J. Besag,et al.  On conditional and intrinsic autoregressions , 1995 .

[7]  P. Guttorp,et al.  Space-time estimation of grid-cell hourly ozone levels for assessment of a deterministic model , 1998, Environmental and Ecological Statistics.

[8]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[9]  Wendy D. Graham,et al.  Optimal estimation of residual non–aqueous phase liquid saturations using partitioning tracer concentration data , 1997 .

[10]  Akhil Datta-Gupta,et al.  Integrating dynamic data into high-resolution reservoir models using streamline-based analytic sensitivity coefficients , 1999 .

[11]  Mike West,et al.  Markov Random Field Models for High-Dimensional Parameters in Simulations of Fluid Flow in Porous Media , 2002, Technometrics.

[12]  R. Kohn,et al.  On Gibbs sampling for state space models , 1994 .

[13]  H. J. Thiébaux,et al.  Spatial objective analysis : with applications in atmospheric science , 1987 .

[14]  David Higdon,et al.  Non-Stationary Spatial Modeling , 2022, 2212.08043.

[15]  M. West,et al.  Bayesian forecasting and dynamic models , 1989 .

[16]  W. Yeh.  Review of Parameter Identification Procedures in Groundwater Hydrology: The Inverse Problem , 1986 .

[17]  D. Oliver,et al.  Markov chain Monte Carlo methods for conditioning a permeability field to pressure data , 1997 .

[18]  Akhil Datta-Gupta,et al.  In-Situ Characterization of Residual NAPL Distribution Using Streamline-Based Inversion of Partitioning Tracer Tests , 1999 .

[19]  Akhil Datta-Gupta,et al.  A new approach to seismic data integration during reservoir characterization using optimal non‐parametric transformations , 1996 .

[20]  Montserrat Fuentes,et al.  A new class of nonstationaryspatial models , 2001 .

[21]  Roger Woodard,et al.  Interpolation of Spatial Data: Some Theory for Kriging , 1999, Technometrics.