Chang-Wan Kang

Data-Dependent Choice of Optimal Number of Lags in Variogram Estimation

Abstract Geostatistical data among spatial data is analyzed in three stages: (1) variogram estimation, (2) model tting for the estimated variograms and (3) spatial prediction using the tted variogram model. It is veryimportant to estimate the variograms properly as the rst stage(i.e., variogram estimation) a ects the nexttwo stages. In general, the variogram is estimated with the moment estimator. To estimate the variogram,we have to decide the ‘lag increment’ or the ‘number of lags’. However, there is no established rule forselecting the number of lags in estimating the variogram. The present paper proposes a method of choosingthe optimal number of lags based on the PRESS statistic. To show the usefulness of the proposed method,we perform a small simulation study and show an empirical example with with air pollution data from Korea. Keywords: Variogram, lag increment, number of lags, optimal lag, default lag. 1. Introduction Geostatistical data among spatial data, also termed random eld data, consists of observationsmeasured at known speci c locations or within speci c regions. Because there are innumerable sit-uations in which data are collected at various locations in space, application elds of spatial statisticsare extensive. For example, the application elds include geology, soil science, image processing,epidemiology, crop science, ecology, forestry, astronomy, atmospheric science and environmentalscience. For these elds, practically, many studies have been carried out. A representative exam-ple of how to use geostatistics in environmental problems is given by Journel (1984). Istok andCooper (1988) demonstrated how to predict ground contaminant concentrations using geostatisticsand Myers (1984) implemented it to assess the movement of a multi-pollutant plume. Furthermore,Webster (1985) investigates soil characteristics and Piazza et al. (1981) analyse gene frequencies.The analysis of such data is carried out in three stages: (1) estimating variograms, (2) ttingvariogram models to the estimated variograms and (3) predicting the value at a speci ed location

A Comparative Study on Spatial Lattice Data Analysis - A Case Where Outlier Exists -

Recently, researchers of the various fields where the spatial analysis is needed have more interested in spatial statistics. In case of data with spatial correlation, methodologies accounting for the correlation are required and there have been developments in methods for spatial data analysis. Lattice data among spatial data is analyzed with following three procedures: (1) definition of the spatial neighborhood, (2) definition of spatial weight, and (3) the analysis using spatial models. The present paper shows a spatial statistical analysis method superior to a general statistical method in aspect estimation by using the trimmed mean squared error statistic, when we analysis the spatial lattice data that outliers are included. To show validation and usefulness of contents in this paper, we perform a small simulation study and show an empirical example with a criminal data in BusanJin-Gu, Korea.

A Development Study of Tool for Web Log Analysis

Recently, many data of various types is gained with development of computer in many fields. Especially, web log data generating in web site furnish beneficial information on an organization. The enterprises destiny is swayed by according as how these information gaining from the web site utilize. In this paper, for the purpose of obtaining useful information, we present a tool is called WebBizi for web log analysis. This will be helpful to enterprise working the web site.