Publications by Zach Herold, Anthony Pagan, Betsy Rosalen
ARIMA Models
Figure 8.31 shows the ACFs for 36 random numbers, 360 random numbers and 1,000 random numbers. 1) ACF (a) Explain Differences Explain the differences among these figures. Do they all indicate that the data are white noise? In each figure the h or maximum lag is 20 and the T or number of observations are increasing. For the data to be white noi...
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LDA and QDA
BB Week 7 https://datascienceplus.com/how-to-perform-logistic-regression-lda-qda-in-r/ library(MASS) library(ggplot2) library(ISLR) attach(Smarket) #Check Dimensions dim(Smarket) ## [1] 1250 9 #Check for missing values apply(Smarket, 2, function(x) {length(unique(x))}) ## Year Lag1 Lag2 Lag3 Lag4 Lag5 Vo...
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Exponential Smoothing
1 Consider the pigs series — the number of pigs slaughtered in Victoria each month. (a) Use the ses() function in R to and the optimal values of @ and lo , and generate forecasts for the next four months. ## Point Forecast Lo 80 Hi 80 Lo 95 Hi 95 ## Sep 1995 98816.41 85605.43 112027.4 78611.97 119020.8 ## Oct 1995 ...
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Data Pre-Procession
3.1 The UC Irvine Machine Learning Repository6 contains a data set related to glass identification. The data consist of 214 glass samples labeled as one of seven class categories. There are nine predictors, including the refractive index and percentages of eight elements: Na, Mg, Al, Si, K, Ca, Ba, and Fe. The data can be accessed via: ## 'data.f...
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Forecasting
Excercise 3.1 For the following series, find an appropriate Box-Cox transformation in order to stabilise the variance. usnetelec usgdp mcopper enplanements lambda<-BoxCox.lambda(usnetelec) autoplot(BoxCox(usnetelec, lambda)) lambda ## [1] 0.5167714 lambda<-BoxCox.lambda(usgdp) autoplot(BoxCox(usgdp, lambda)) lambda ## [1] 0.366352 lambda<-Box...
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Time Series
Excercise 2.1 A Use the help function to explore what the series gold, woolyrnq and gas represent. #(gold) #?woolyrnq #?gas glimpse(gold) ## Time-Series [1:1108] from 1 to 1108: 306 300 303 297 304 ... glimpse(woolyrnq) ## Time-Series [1:119] from 1965 to 1994: 6172 6709 6633 6660 6786 ... glimpse(gas) ## Time-Series [1:476] from 1956 to ...
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Data 608 Final Project
Overview The societal impact of income inequality is well known. Can school clubs, sports and other after school programs shape a childs future who otherwise would not be exposed to the positive influences additional school activities can bring? Objective In this data anaylsis we try to answer the question What is the impact of children who are ...
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Data 621 ELMR Exercise 11.5
Smooth Plots Code used in analysis knitr::opts_chunk$set( echo = FALSE, message = FALSE, warning = FALSE ) #ELMR 11.5 library(sm) library(faraway) data('aatemp') attach(aatemp) par(mfrow=(c(2,3))) plot(temp ~ year, aatemp,main="bandwidth=0.1",pch=".") lines(ksmooth(year,temp,"normal",0.1)) plot(temp ~ year, aatemp,main="...
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Data 621 ELMR Exercise 9.3
Smooth Plots Code knitr::opts_chunk$set( echo = FALSE, message = FALSE, warning = FALSE ) #ELMR 11.5 library(sm) library(faraway) data('aatemp') attach(aatemp) par(mfrow=(c(2,3))) plot(temp ~ year, aatemp,main="bandwidth=0.1",pch=".") lines(ksmooth(year,temp,"normal",0.1)) plot(temp ~ year, aatemp,main="bandwidth=0.5",pc...
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Publish Document
OVERVIEW The societal impact of income is well known. Can sports shape a childs life who otherwise would not be exposed to the positive influences and challenges that sports can bring. Objective In this data anaylsis we try to answer the question What is the future impact for children who play sports vs children that do not play sports? Approac...
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