Publications by Travis Compton
Time Series Analysis
Exercise 1 For simulated stationary data (n=200) under different ARMA models listed below, (i) plot observations, (ii) plot its ACF and PACF plots, and (iii) describe what you observe from ACF and PACF. a) Two sets of simulated stationary data under AR(3) model by specifying coefficients (𝜙1,𝜙2,𝜙3) with your choice For ar3.1 and ar3.2 ...
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Fundraising Classification Prediction.
Reading in the data fundraising = read_rds('fundraising.rds') future.predict = read_rds("future_fundraising.rds") Creating validation set from fundraising data set set.seed(12345) index = sample(1:nrow(fundraising), 0.8*nrow(fundraising)) train.fund = fundraising[index,] val.fund = fundraising[-index,] str(fundraising) ## tibble[,21] [3,000 ...
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Time Series Analysis Cont.
Exercise 1: Seasonal ARIMA Use the “Electricity.RData” examined in HW1 Exercise 2 (d)-(f). Fit the model using first order differenced log transformed series. ###(a) By visually checking, decide what SARIMA models seem appropriate, i.e., specify p, d, q and P,D, Q in SARIMA model, ARIMA(p, d, q) ∗ ARIMA(P,D, Q)𝑠. Choose the most appropri...
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Working with Support Vector Machine
5. We have seen that we can fit an SVM with a non-linear kernel in order to perform classification using a non-linear decision boundary. We will now see that we can also obtain a non-linear decision boundary by performing logistic regression using non-linear transformations of the features. (a) Generate a data set with n = 500 and p = 2, such th...
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Using decision trees and random forest.
3. Consider the Gini index, classification error, and cross-entropy in a simple classification setting with two classes. Create a single plot that displays each of these quantities as a function of ˆpm1. The x axis should display ˆpm1, ranging from 0 to 1, and the y-axis should display the value of the Gini index, classification error, and entr...
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ISLR Chapter 7 - Moving Beyond Linearity
head(Wage) ## year age maritl race education region ## 231655 2006 18 1. Never Married 1. White 1. < HS Grad 2. Middle Atlantic ## 86582 2004 24 1. Never Married 1. White 4. College Grad 2. Middle Atlantic ## 161300 2003 45 2. Married 1. White 3. Some College 2. Middle Atlantic ## 155159 200...
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Time Series Analysis
load("cregist.RData") train.cregist = ts(cregist[1:223], frequency = 4, start = c(1960,1)) test.cregist = ts(cregist[224:235], frequency = 4) Question 1 The “cregist.RData” contains quarterly observed passenger car registration (units) in the United States from January 1960 to July 2018. Data is from FRED (Federal Reserve Economic Data) an...
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