Modern statistical methods for spatial and multivariate data

Modern statistical methods for spatial and multivariate data

by Diawara, Norou

Type Book
Rate 0.0 /5

This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in …

Read More ↓

Title Statements

  • Full title :Modern statistical methods for spatial and multivariate data / Norou Diawara, editor.

Summary

This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.--

Read More ↓

Edition Statements

  • Publication Date:©2019

Publication Statements

  • Publisher(s):Springer
  • Place of Publication:Cham, Switzerland
  • Language:eng
  • Publication Date:©2019

The Physical Object

  • Description:1 online resource : : illustrations

Edition Identifiers

  • ISBN:9783030114312, 3030114317, 3030114309, 9783030114305, 9783030114329, 3030114325
  • DOI:10.1007/978-3-030-11431-2
  • oclc:on1107041840
  • LC Classification:QA276
  • Dewey Decimal:519

Table of Contents

A. Working, M. Alqawba, and N. Diawara: Functional Form of Markovian Attribute-level Best-Worst Discrete Choice Modelling -- D. Hitchcock, H. Liu, and S. Zahra Samadi -- Spatial and Spatio-temporal Analysis of Precipitation Data from South Carolina -- D. Musgrove, D. Young, J. Hughes, and L.E. Eberly: A sparse areal mixed model for multivariate outcomes, with an application to zero-inflated Census data -- E.M. Maboudou-Tchao: Wavelet Kernels for Support Matrix Machines -- S.A. Janse and K.L. Thompson: Properties of the number of iterations of a feasible solutions algorithm -- R. Dey and M.S. Mulekar: A Primer of Statistical Methods for Classification -- M. Sheth-Chandra, N.R. Chaganty, and R.T. Sabo: A Doubly-Inflated Poisson Distribution and Regression Model -- J. Mathews, S. Sen, and I. Das: Multivariate Doubly-Inflated Negative Binomial Distribution using Gaussian Copula -- J. Lorio, N. Diawara, and L. Waller: Quantifying spatio-temporal characteristics via Moran's statistics.

Read More ↓

Subjects

Writers

More from this Series

  • New trends and advanced methods in interdisciplinary mathematical sci…

    ©2017
    more →
    New trends and advanced methods in interdisciplinary mathematical sciences
  • Modern statistical methods for spatial and multivariate data

    2019
    more →
    Modern statistical methods for spatial and multivariate data
  • Innovative integrals and their applications I

    2022.
    more →
    Innovative integrals and their applications I

Rate & Review

0.0/5
(0 people Voted)

No reviews yet. Be the first to rate this work.

Files & Downloads

No downloadable files are registered for this work yet.