Publications by STA570: Time Series Analysis and Forecasting
Model Estimation Procedure
Loading Require Packages library (dynlm) ## Warning: package 'dynlm' was built under R version 3.5.3 ## Loading required package: zoo ## Warning: package 'zoo' was built under R version 3.5.3 ## ## Attaching package: 'zoo' ## The following objects are masked from 'package:base': ## ## as.Date, as.Date.numeric Data Preparation Down...
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Econometric Models using R
Introduction The following examples describe some of the commonly used statistical testing procedures by using R Programming. We will use several data sets as example for each statistical testing procedures. library (dynlm) ## Warning: package 'dynlm' was built under R version 3.5.3 ## Loading required package: zoo ## Warning: package 'zoo' w...
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Basic Data Summary and Visualization in R
Basic Visualization in R Programming: Base Package Data Preparation Before we begin, make sure that you read the dataset ‘telco.csv’ into your R console. There are two ways of doing it; Read the csv file by using read.csv and put the function file.choose () into the read.csv function, and name the data as telco_data; telco_data <- read.c...
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Basic Inferential Statistics
Data Preparation telco_data <- read.csv ("telco.csv", stringsAsFactors = TRUE) Inferential Statistics Assumptions of Normality It is important for us to recognize the shape of our data distribution. It will determine the appropriate statistical methods use to analyze the data. Generally, we will see whether our datasets; i. Symmetrical (bell...
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BoxJenkins Method
library(tseries) ## Warning: package 'tseries' was built under R version 4.0.2 library(forecast) library(readxl) Data Preparation (Textbook Example) CPI, Monthly Road Accidents and Palm Oil Production dataset will be used in this example. The datasets are provided, and please download and save the file into your R directory. To make it easy for...
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Topic 3: Econometric Models
Topic 3: Econometric Modelling In this topic you will learn; 3.1 Introduction to R Programming 3.2 Econometric Model Definition 3.3 Model Construction Issues 3.4 The Assumption 3.5 Validation and Testing and 3.6 Model Estimation Procedure. If you view by using web, please choose the tab accordingly; 3.1 Introduction to R Programming R is ...
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