Publications by PS
Dimensionality Reduction
Part 1: Multicollinearity What is Multicollinearity? One of the reasons we use variable reduction techniques is the multicollinearity. Multicollinearity exists in the case of highly correlated independent variables. Because these variables move similarly, it will not be easy to distinguish their effect on the predicted variable. If you try to ...
7737 sym 4 img
Time Series III
Part 1: ARIMA Models in R Step 1: In the first part of this week seminar you will see how to employ ARIMA models in R. For that purpose, we will use the forecast package. You have already installed the package from previous weeks. The only step you need to do is to load the library. Task: Load library forecast. Step 2: For the purpose of this...
11472 sym Python (3253 sym/7 pcs) 8 img 1 tbl
Time Series III
Part 1: ARIMA Models in R Step 1: In the first part of this week seminar you will see how to employ ARIMA models in R. For that purpose, we will use the forecast package. You have already installed the package from previous weeks. The only step you need to do is to load the library. Task: Load library forecast. Step 2: For the purpose of this...
9635 sym Python (3253 sym/7 pcs) 8 img
Document
Multiple Linear Regression Multiple linear regression is a linear regression with more than one predictor variables. It produces a model that identifies the best weighted combination of the independent variables to predict the forecast variable. In R, it is used in the exact same way as the simple linear regression. Getting Familiar with the d...
9996 sym R (2947 sym/14 pcs) 2 img 3 tbl
SEM
First you need to install and load the required package Lavaan.Then you need to load the dataset for the first part of the seminar. This is found on minerva path.csv. # Add packages to Library library("lavaan") ## This is lavaan 0.6-15 ## lavaan is FREE software! Please report any bugs. # Load data dat <- read.csv("path.csv") What is SEM ? St...
10599 sym R (12697 sym/13 pcs) 7 img
Lecture 10
2023-04-24 R Markdown This is an R Markdown presentation. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com. When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code c...
472 sym 1 img
Text Analytics
Text Analytics First you need to install and load all the packages needed. #install.packages("tm") #install.packages("tokenizers") #install.packages("SnowballC") #install.packages("textstem") #install.packages('gutenbergr') # Add packages to Library library(tm) library(tokenizers) library(textstem) library(gutenbergr) Basic of Text Corp...
10295 sym R (10828 sym/66 pcs) 4 img 3 tbl
Survival Analysis
Survival Analysis First we need to install the required packages survival and dplyr. install.packages("survival") install.packages("dplyr") # Add packages to Library library("survival") library("dplyr") Survival and Hazard Function Now in our example we will explore the time until phone contract cancellations. let’s create two vectors. Th...
7006 sym R (11592 sym/35 pcs) 7 img
Variable Reduction
Part 1: Multicollinearity What is Multicollinearity? One of the reasons we use variable reduction techniques is multicollinearity. Multicollinearity exists in the case of highly correlated independent variables. Because these variables move similarly, it will not be easy to distinguish their effect on the predicted variable. If you try to model a ...
9369 sym 4 img
Variable Reduction
Part 1: Multicollinearity What is Multicollinearity? One of the reasons we use variable reduction techniques is multicollinearity. Multicollinearity exists in the case of highly correlated independent variables. Because these variables move similarly, it will not be easy to distinguish their effect on the predicted variable. If you try to mode...
9506 sym 4 img