Linear interpolation and joint model fitting of experimental transiograms for Markov chain simulation of categorical spatial variables
نویسندگان
چکیده
Key Laboratory of Subtropical Agriculture Resource and Environment, Ministry of Agriculture, College of Resource and Environment, Huazhong Agricultural University, Wuhan, Hubei, China; Department of Resource and Environmental Information Science and Engineering, Huazhong Agricultural University, Wuhan, Hubei, China; Department of Geography and Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, CT, USA
منابع مشابه
A Generalized Markov Chain Approach for Conditional Simulation of Categorical Variables from Grid Samples
Complex categorical variables are usually classified into many classes with interclass dependencies, which conventional geostatistical methods have difficulties to incorporate. A two-dimensional Markov chain approach has emerged recently for conditional simulation of categorical variables on line data, with the advantage of incorporating interclass dependencies. This paper extends the approach ...
متن کاملTransiogram: A spatial relationship measure for categorical data
Categorical geographical variables are normally classified into multinomial classes which are mutually exclusive and visualized as area-class maps. Typical categorical variables such as soil types and land cover classes are multinomial and exhibit complex interclass relationships. Interclass relationships may include three situations: cross-correlation (i.e. interdependency), neighbouring situa...
متن کاملModeling experimental cross-transiograms of neighboring landscape categories with the gamma distribution
Effectively fitting the major features of experimental transiograms (or variograms) is crucial in characterizing spatial patterns and reproducing them in geostatistical simulations. Landscape patterns usually tend to contain neighboring structures. The experimental cross-transiograms of frequent neighboring landscape categories normally demonstrate apparent peaking features at low lag distances...
متن کاملOptimal Interpolation and the Appropriateness of Cross-Validating Variogram in Spatial Generalized Linear Mixed Models
In this work, we consider some computational issues related to the minimum mean-squared error (MMSE) prediction of non-Gaussian variables under a spatial generalized linear mixed model (GLMM). This model has been used to model spatial non-Gaussian variables by Diggle et al. (1998) and Zhang (2002), under which MMSE prediction of non-Gaussian variables can be computed. Since the MMSE prediction ...
متن کاملBayesian Density Regression through Projections
We explore a Bayesian density regression model driven by linear projections of covariates. This offers an alternative to variable selection and provides the best linear compression of covariates for predicting a response in a regression setting. We provide a detailed construction of our probabilistic model based on smooth Gaussian processes and uniformly distributed linear subspaces. We prove p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- International Journal of Geographical Information Science
دوره 24 شماره
صفحات -
تاریخ انتشار 2010