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Using R for Trade Policy Analysis

Using R for Trade Policy Analysis

Massimiliano Porto

Springer International Publishing AG
2023
sidottu
This book explains the best practices of the UNCTAD & WTO for trade analysis to the R users community. It shows how to replicate the UNCTAD & WTO's Stata codes in the Practical Guide to Trade Policy Analysis by using R. Applications and exercises are chosen from the Practical Guide to Trade Policy Analysis and explain how to implement the codes in R. This books targets readers with a basic knowledge of R. It is particularly suitable for Stata users. This edition has been updated and expanded to include updated R code and visualization tools.
Using R for Trade Policy Analysis

Using R for Trade Policy Analysis

Massimiliano Porto

Springer International Publishing AG
2024
nidottu
This book explains the best practices of the UNCTAD & WTO for trade analysis to the R users community. It shows how to replicate the UNCTAD & WTO's Stata codes in the Practical Guide to Trade Policy Analysis by using R. Applications and exercises are chosen from the Practical Guide to Trade Policy Analysis and explain how to implement the codes in R. This books targets readers with a basic knowledge of R. It is particularly suitable for Stata users. This edition has been updated and expanded to include updated R code and visualization tools.
Using R for Digital Soil Mapping

Using R for Digital Soil Mapping

Brendan P. Malone; Budiman Minasny; Alex B. McBratney

Springer International Publishing AG
2016
sidottu
This book describes and provides many detailed examples of implementing Digital Soil Mapping (DSM) using R. The work adheres to Digital Soil Mapping theory, and presents a strong focus on how to apply it. DSM exercises are also included and cover procedures for handling and manipulating soil and spatial data in R. The book also introduces the basic concepts and practices for building spatial soil prediction functions, and then ultimately producing digital soil maps.
Using R for Digital Soil Mapping

Using R for Digital Soil Mapping

Brendan P. Malone; Budiman Minasny; Alex B. McBratney

Springer International Publishing AG
2018
nidottu
This book describes and provides many detailed examples of implementing Digital Soil Mapping (DSM) using R. The work adheres to Digital Soil Mapping theory, and presents a strong focus on how to apply it. DSM exercises are also included and cover procedures for handling and manipulating soil and spatial data in R. The book also introduces the basic concepts and practices for building spatial soil prediction functions, and then ultimately producing digital soil maps.
Practicing R for Statistical Computing

Practicing R for Statistical Computing

Muhammad Aslam; Muhammad Imdad Ullah

SPRINGER VERLAG, SINGAPORE
2023
sidottu
This book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation. It covers fundamental data structures such as vectors, matrices, arrays and lists, along with techniques for exploratory data analysis, data transformation and manipulation. The book explains basic statistical concepts and demonstrates their implementation using R, including descriptive statistics, graphical representation of data, probability, popular probability distributions and hypothesis testing. It also explores linear and non-linear modeling, model selection and diagnostic tools in R. The book also covers flow control and conditional calculations by using ‘‘if’’ conditions and loops and discusses useful functions and resources for further learning. It provides an extensive list of functions grouped according to statistics classification, which can be helpful for both statisticians and R programmers. The use of different graphic devices, high-level and low-level graphical functions and adjustment of parameters are also explained. Throughout the book, R commands, functions and objects are printed in a different font for easy identification. Common errors, warnings and mistakes in R are also discussed and classified with explanations on how to prevent them.
Practicing R for Statistical Computing

Practicing R for Statistical Computing

Muhammad Aslam; Muhammad Imdad Ullah

SPRINGER VERLAG, SINGAPORE
2024
nidottu
This book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation. It covers fundamental data structures such as vectors, matrices, arrays and lists, along with techniques for exploratory data analysis, data transformation and manipulation. The book explains basic statistical concepts and demonstrates their implementation using R, including descriptive statistics, graphical representation of data, probability, popular probability distributions and hypothesis testing. It also explores linear and non-linear modeling, model selection and diagnostic tools in R. The book also covers flow control and conditional calculations by using ‘‘if’’ conditions and loops and discusses useful functions and resources for further learning. It provides an extensive list of functions grouped according to statistics classification, which can be helpful for both statisticians and R programmers. The use of different graphic devices, high-level and low-level graphical functions and adjustment of parameters are also explained. Throughout the book, R commands, functions and objects are printed in a different font for easy identification. Common errors, warnings and mistakes in R are also discussed and classified with explanations on how to prevent them.