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  • Quantitative methods : regression analysis
  • Model selection in analyzing spatial groups in regression analysis
  • Anisotropic variance functions in geographically weighted regression models
  • Analysis of variance ; Distance ; Model ; Regression analysis ; Spatial analysis ; Statistics
  • Diagnostics for regression modeling in spatial econometrics
  • Distance ; Econometry ; Error ; Estimation ; Matrix analysis ; Modelling ; Regression analysis ; Space time ; Spatial analysis ; Statistics
  • A study of variations of diurnal suns of precipitation by means of regression analysis
  • The method of regression analysis is verified in variations of diurnal sums of precipitation of the summer season at 50 stations on the territory of Czechoslovakia in the years 1901-1975. The used processing shows that even considerably distance
  • The use of added variable plots in regression modelling with spatial data
  • Correlation ; Data analysis ; Linear regression ; Mathematical model ; Model ; Multivariate analysis ; Regression analysis ; Spatial analysis
  • Ein Verfahren zur Aufstellung statistischer Prognosealgorithmen als Einheit von Cluster-, Diskriminanz- und Regressionsanalyse (A method for the development of statistical forecasting algorithms including cluster, discriminance and regression
  • analysis)
  • The method presented by the author is used to develop a large number of predictors within a system of multiple regression equations with a series of classifications. The method includes an ideal classification, a screening discriminance analysis
  • and a stepwise, multiple, regression analysis based upon the cross-validation technique. - (IH)
  • Weighted bidimensional regression
  • Landmark ; Matrix analysis ; Methodology ; Regression analysis ; Weighted
  • Extrapolation ; Lake ; Quantitative analysis ; Regression analysis ; Sweden
  • The basic aim is, to provide an estimate of the number of lakes in Sweden. The method to do this concerns transformations, regressions and extrapolations.
  • Regression analysis and geographic models
  • Applying principal components regression analysis to time series demand estimation
  • Biaised statistics with zero observations in multiple regression analysis of regional data
  • Bidimensional regression
  • Calibration ; Cartography ; Error ; Least squares method ; Linear regression ; Matrix analysis ; Regression analysis ; Spatial statistics ; Statistics
  • Multiattribute shopping models and ridge regression analysis
  • Commerce de détail ; Comportement ; Comportement d'achat ; Géographie humaine ; Interaction spatiale ; Localisation ; Modèle ; Méthodologie ; Ridge regression
  • technique de la ridge regression pour pallier ces problèmes. Application à un modèle d'interaction du comportement spatial d'achat.
  • Spurious spatial regression : some Monte Carlo results with a spatial unit root and spatial cointegration
  • Error ; Matrix analysis ; Monte Carlo analysis ; Regression analysis ; Spatial analysis ; Statistics
  • Comparative spatial filtering in regression analysis
  • Methodology ; Regression analysis ; Spatial analysis ; Spatial autocorrelation ; Spatial statistics
  • Evaluation of human bioclimates using quantile regression : a China case study
  • Bioclimatology ; Cartography ; China ; Climatic index ; Clothing ; Comfort ; Human bioclimatology ; Regression analysis ; Spatial distribution ; Temperature
  • A nonparametric version of quantile regressions was applied to investigate the human bioclimates in China through the use of the CLO (clothing requirements) index. Quantile regression surface maps produced from the whole spectrum of the CLO
  • distribution provided better insights into the spatial characteristics of clothing requirements and information on the spread and variations of the distribution. Univariate quantile regression were constructed to display the temporal variability of CLO
  • at different locations. Hence, this analysis produced a more complete picture of the human bioclimates of the various regions in China.
  • Comparison of landslide susceptibility maps generated through multiple logistic regression for three test areas in Korea
  • Cartography ; Geographical information system ; LANDSAT ; Landslide ; Natural hazards ; Regression analysis ; Remote sensing ; Slope ; South Korea ; Thematic Mapper
  • The aim of this study was to apply, verify and compare a multiple logistic regression model for landslide susceptibility analysis in 3 Korean study areas using a geographic information system (GIS). Landslide locations were identified
  • the database and the logistic regression coefficient of each factor was computed. Landslide susceptibility maps were drawn for these 3 areas using logistic regression coefficients.
  • The modifiable areal unit problem in multivariate statistical analysis
  • In an investigation of the parameter estimates from a multiple linear regression model and a multiple logit regression model, conclusions are drawn about the sensitivity of such estimates to variations in scale and zoning systems. There is strong
  • evidence of the unreliability of any multivariate analysis undertaken with data from areal units.
  • This study offers an example of regression following factor analysis. In substituting correspondence analysis for the principal components analysis of Imbrie and Kipp, the A. improves on the results of them: firtsly, he obtains higher correlation
  • coefficients| and secondly he calculates these coefficients from a more appropriate reference sample, from which a more exact estimation of the quality of the regression is obtained.