Publications by Gabriella Martinez
Ordinal Logisitic Regression
Ordinal Logisitic Regression For this code along, I will be using the UCLA R Data Analysis Example1 to explore the polr function from the MASS package used to perform an ordinal logisitc regression and give a brief overview of its usage. As such, key components usually conducted in the research process will not be included such as data cleaning, ...
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Dimensionality Reduction and Billboard Top 100
TidyTuesday 09-14-2021 What is TidyTuesday? Before going into the code along to Julia Silge’s screencast1 2, TidyTuesday is a weekly social data project using the R programming language. For those unfamiliar with what “tidy” data is, looks like, and how to do it, Tidy Data and tidyr YouTube video3 is a gentle introduction to data wrangling...
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Preliminary HW3
Binary Logistic Regression Overview In this homework assignment, you will explore, analyze and model a data set containing information on crime for various neighborhoods of a major city. Each record has a response variable indicating whether or not the crime rate is above the median crime rate (1) or not (0). Your objective is to build three dif...
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Preliminary HW4
library(tidyverse) library(ggplot2) library(mice) library(car) library(Hmisc) library(corrplot) library(pscl) library(boot) library(caret) library(leaps) library(MASS) library(kableExtra) library(summarytools) library(stats) library(olsrr) Load data # Load TRAIN insurance csv df_ins_raw <- read.csv("https://raw.githubusercontent.c...
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Multinomial Logistic Regression
Multinomial Logisitic Regression What is it? Multinomial Logistic Regression is an extension of binomial logistic regression. Binomial Logistic Regression is used to model a binary response variable using a logistic function. Similarly, multinomial logistic regression is used to model categorical response variables with greater than 2 levels usi...
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DATA621 Final
Overview There are millions of stray pets around the world, some of which are fortunate enough to be adopted while many others are not. While adoption of a pet is often the definition of success, the rate at which a pet is adopted is also a key success factor - pets that take a long time to adopt contribute to over-crowded animal shelters and can...
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DATA624 Project 1
Project 1 Instructions This project consists of 3 parts - two required and one bonus and is worth 15% of your grade. The project is due at 11:59 PM on Sunday Apr 3. I will accept late submissions with a penalty until the meetup after that when we review some projects. Packages library(readxl) library(fpp3) library(forecast) library(ggplot2) ...
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DATA624 HW6
Homework 6: ARIMA Instructions Do exercises 9.1, 9.2, 9.3, 9.5, 9.6, 9.7, 9.8 in Forecasting: Principles and Practice. Please submit both your Rpubs link as well as attach the .rmd file with your code. Packages library(fpp3) library(latex2exp) library(ggpubr) Exercises 9.1 Figure 9.32 shows the ACFs for 36 random numbers, 360 random numbers...
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DATA624 HW5
Homework 5: Exponential Smoothing Instructions Do exercises 8.1, 8.5, 8.6, 8.7, 8.8, 8.9 in Forecasting: Principles and Practice. Please submit both your Rpubs link as well as attach the .rmd file with your code. Packages library(fpp3) Exercises 8.1 Consider the the number of pigs slaughtered in Victoria, available in the aus_livestock datase...
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DATA624 HW3
Homework 3: Forecasting Instructions Do exercises 5.1, 5.2, 5.3, 5.4 and 5.7 from Forecasting: Principles and Practice book. Please submit both your Rpubs link as well as attach the .rmd file with your code. Packages library(fpp3) library(fabletools) Naive method NAIVE(y): How it works: sets all forecasts to be the value of the last observati...
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