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Displaying Time Series, Spatial, and Space-Time Data with R

ISBN/GTIN

Displaying Time Series, Spatial, and Space-Time Data with R

von

Perpinan Lamigueiro, Oscar

BuchKartoniert, Paperback

Verkaufsrang16630inMathematik

CHF109.00

E-BookabCHF125.75

In den Warenkorb

Beschreibung

This book will provide methods to display space-time data using R. The code of each method will be detailed and commented through practical examples with real data. The second edition will discuss new interactive R packages and Add introductory sections with easier examples to show the basics of the most important packages and functions

Weitere Beschreibungen

Details

ISBN/GTIN978-1-138-08998-3

ProduktartBuch

EinbandKartoniert, Paperback

VerlagTaylor and FrancisChapman and Hall/CRC

Erscheinungsdatum14.08.2018

Auflage2. A.

ReiheChapman & Hall/CRC The R Series

Seiten272 Seiten

SpracheEnglisch

MasseBreite 156 mm, Höhe 234 mm

Gewicht426 g

IllustrationenFarb., s/w. Abb.

Artikel-Nr.36606767

KatalogBuchzentrum

Datenquelle-Nr.27227724

WarengruppeMathematik

Weitere Details

Reihe

Dealing with Memory Limits and Working with Large Data Sets in R

Statistical Computing with R

R Graphics

Statistical Computing in C++ and R

Event History Analysis with R

Customer and Business Analytics

Programming Graphical User Interfaces in R

Analyzing Baseball Data with R

Implementing Reproducible Research

Stated Preference Methods Using R

Growth Curve Analysis and Visualization Using R

Computational Actuarial Science with R

Multiple Factor Analysis by Example Using R

Analyzing Sensory Data with R

Displaying Time Series, Spatial, and Space-Time Data with R

Using R for Numerical Analysis in Science and Engineering

Advanced R

Introduction to Scientific Programming and Simulation Using R

Using R for Introductory Statistics

Data Science in R

Parallel Computing for Data Science

Dynamic Documents with R and knitr

Statistics in Toxicology Using R

Graphical Data Analysis with R

Reproducible Research with R and R Studio

Introductory Fisheries Analyses with R

Using the R Commander

bookdown

Spatial Microsimulation with R

The Essentials of Data Science: Knowledge Discovery Using R

R Primer

Dynamic Documents with R and knitr

Reproducible Research with R and R Studio

Extending R

bookdown

Using the R Commander

Customer and Business Analytics

R Primer

blogdown

Flexible Regression and Smoothing

Data Science in R

R Markdown

Reproducible Finance with R

Practical R for Mass Communication and Journalism

Practical R for Mass Communication and Journalism

Displaying Time Series, Spatial, and Space-Time Data with R

Statistical Computing with R, Second Edition

Hands-On Machine Learning with R

Advanced R, Second Edition

Advanced R, Second Edition

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Reproducible Research with R and RStudio

Learn R

Learn R

Learning Microeconometrics with R

Geocomputation with R

Digital Media

Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

Interactive Documents with R

Engineering Production-Grade Shiny Apps

Engineering Production-Grade Shiny Apps

Javascript for R

Javascript for R

Advanced R Solutions

Advanced R Solutions

Dose-Response Analysis Using R

Statistics in Toxicology Using R

Distributions for Modeling Location, Scale, and Shape

Event History Analysis with R

Outstanding User Interfaces with Shiny

Outstanding User Interfaces with Shiny

Rasch Measurement Theory Analysis in R

Rasch Measurement Theory Analysis in R

Spatial Sampling with R

A Criminologist's Guide to R

R for Political Data Science

ANOVA and Mixed Models

ANOVA and Mixed Models

Open Science with R

Spatial Data Science

Starting Quantitative Analysis with R

Analyzing US Census Data

Analyzing US Census Data

Deep Learning and Scientific Computing with R torch

Tidy Finance with R

Model-Based Clustering, Classification, and Density Estimation Using mclust in R

Graphical Data Analysis with R

Statistical Computing in C++ and R

Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

Modern Data Visualization with R

Modern Data Visualization with R

Learn R

Learn R

Behavior Analysis with Machine Learning Using R

Event History Analysis with R

Spatial Analysis in Geology Using R

Analyzing Baseball Data with R

Analyzing Baseball Data with R

Introductory Fisheries Analyses with R

Multiple Factor Analysis by Example Using R

Über den/die AutorIn

Perpinan Lamigueiro, Oscar

Oscar Perpiñán-Lamigueiro is an Associate Professor at the Universidad Politécnica de Madrid, involved in teaching and research of Electrical Engineering, Electronics and Programming. He is also a lecturer of Photovoltaic and Solar Energy at the Escuela de Organización Industrial. He holds a Master's Degree in Telecommunications Engineering and a PhD in Industrial Engineering. At present, his research focuses on solar radiation (forecasting, spatial interpolation, open data) and software development with R (packages rasterVis, solaR, meteoForecast, PVF, tdr).

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