###### GI DL - GPU-based regressionanalysis on sparse grids
Regression analysis enables to predict easily based on given data. This paper focuses on regression analysis on sparse grids ... Hirschmann, S., (2014). GPU-based regression analysis on sparse grids. In: Plödereder, E., Grunske, L., Schneider, E. & Ull, D ... title = {GPU-based regression analysis on sparse grids},. booktitle = {Informatik 2014},. year = {2014},. editor = {Plödereder ... The core workload of the regression analysis will be implemented on graphics cards using NVIDIA's Compute Unified Device ... https://dl.gi.de/handle/20.500.12116/2880
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###### Implement Seemingly Unrelated RegressionAnalyses
... This example will be removed in a future release. ... This example shows how to prepare exogenous data for several seemingly unrelated regression (SUR) analyses. The response and ... the number of regression variables (. 'nX'. ), and whether to include different regression intercepts for each response series ... and specifying the number of response series and the number of regression variables. By default, vgxset. excludes regression ... http://www.mathworks.com/examples/econometrics/mw/econ-ex83533901-implement-seemingly-unrelated-regression-analyses
###### Applied RegressionAnalysis - Norman Richard Draper - Google Books
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###### Introduction to RegressionAnalysis (Montreal, QC)
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###### Regressionanalysis sample size problem | Physics Forums
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###### RegressionAnalysis for Spatial Data (Boulder, CO)
... spatial regression models (SAR and SEM), geographically weighted regression (GWR), and conditional autoregressive models (CAR ... Tags: spatial autocorrelation, spatial regression, spatial error, spatial lag, LISA, R, GeoDa ... Software emphasis will be given to GeoDa and R for exploratory spatial data analysis and modeling. Some acquaintance with this ... Prerequisites: Prerequisites for maximizing learning in this course are a solid grounding in standard multivariate regression ... https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0029
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