Publications by Jack Wright
preprocessing hw
Preprocessing/Overfitting Homework Jack Wright 3.1, 3.2 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,...
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Time-Series
Timeseries Data 624 Jack Wright 2.1 Use the help function to explore what the series gafa_stock, PBS, vic_elec and pelt represent. a.Use autoplot() to plot some of the series in these data sets. b.What is the time interval of each series? Lets do some EDA on the datasets provided gafa_stock #help(gafa_stock) gafa_stock are historical stock pri...
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hw_2_predictive
Time Series Decomposition Homework Jack Wright 3.1, 3.2, 3.3, 3.4, 3.5, 3.7, 3.8 and 3.9 3.1 Consider the GDP information in global_economy. Plot the GDP per capita for each country over time. Which country has the highest GDP per capita? How has this changed over time? ⊕countries with highest mean gdp per capita across all years Country me...
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Capstone Idea
Time Series Decomposition Homework Jack Wright Introduction The research team headed by Dr Colette Daiute at the CUNY Grad Center is conducting a followup research project to their 2018 study, “Meta-Communication Between Designers and Players of Interactive Digital Narratives.” This study addresses quantitatively analysing “meta-communicatio...
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Toolbox HW
Time Series Decomposition Homework Jack Wright 5.1, 5.2, 5.3, 5.4 and 5.7 5.1 Produce forecasts for the following series using whichever of NAIVE(y), SNAIVE(y) or RW(y ~ drift()) is more appropriate in each case:Australian Population (global_economy) Bricks (aus_production) NSW Lambs (aus_livestock) Household wealth (hh_budget) Australian Popula...
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Exponential Smoothing Homework
Exponential Smoothing Homework Jack Wright 8.1, 8.5, 8.6, 8.7, 8.8, 8.9 8.1 Consider the the number of pigs slaughtered in Victoria, available in the aus_livestock dataset. Use the ETS() function to estimate the equivalent model for simple exponential smoothing. Find the optimal values of α and ℓ 0, and generate forecasts for the next four m...
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Lit review 1
This literature review will support the goal of creating a more robust Narrative Tree Complexity Metric for the field of Interactive Digital Narrative Design. To build a case, we will examine: Narrative Theory Complexity Theory Measuring Complexity Pairwise Comparison Use of Complexity in IDN Current state of tree-structure complexity metrics in...
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Simple Linear Regression with Dummy Variable
Requirements for simple linear regression with dummy variable response variable is.continuous(dependent_variable) predictor variable is.binary(predictor_variable) library(tidyverse) library(here) library(AER) data('CASchools') df<-CASchools df<-df%>%dplyr::mutate(STR=as.numeric(students)/as.numeric(teachers)) df<-df%>%mutate(D=STR<20)%>%muta...
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Poisson Distribution
Poisson Distribution expresses the probability of a given number of events occuring in a fixed interval of time or space IF these events occur with a known constant mean rate AND independently Poisson Case examples Probability of occcurrence of an event in a given time interval is proportional to the length of that time interval and independent ...
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Nonlinear Regression Homework
NonLinear Regression Jack Wright 7.2 , 7.5 7.2 Benchmark data set created by simulation. One of the simulations used the following nonlinear equation \[y = 10sin(\pi x_1 x_2)+20(x_3 -0.5)^2+10x_4 + 5x_5 +N(0, \sigma^2)\] x are the values of random variables uniformly distributed between [0,1] 5 non-informative variables also created for simulat...
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