Publications by Adam Gersowitz
Project 2
Project 2 library(caret) ## Loading required package: ggplot2 ## Loading required package: lattice library(readxl) library(tidymodels) ## Registered S3 method overwritten by 'tune': ## method from ## required_pkgs.model_spec parsnip ## ── Attaching packages ────────────────────�...
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Group2 HW4
Overview In this project, we analyze a real-life mental health dataset to provide context around suicide prediction given a variety of unidentifiable demographic data. Our goals are to understand the variables relationships, identify those variables that influence our target, and develop models that can predict a patient’s risk of suicide. App...
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Data 624 HW 8
7.2. Friedman (1991) introduced several benchmark data sets create by sim- ulation. One of these simulations used the following nonlinear equation to create data: y = 10sin(πx1x2)+20(x3 −0.5)2 +10x4 +5x5 +N(0,σ2) where the x values are random variables uniformly distributed between [0, 1] (there are also 5 other non-informative variables a...
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Data 624 HW 7
6.2. Developing a model to predict permeability (see Sect. 1.4) could save significant resources for a pharmaceutical company, while at the same time more rapidly identifying molecules that have a sufficient permeability to become a drug: (a) Start R and use these commands to load the data: > library(AppliedPredictiveModeling) > data(permeabil...
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Data 624 Project 1
Part A - ATM Forecast I want you to forecast how much cash is taken out of 4 different ATM machines for May 2010. The data is given in a single file. The variable ‘Cash’ is provided in hundreds of dollars, other than that it is straight forward. I am being somewhat ambiguous on purpose to make this have a little more business feeling. Explai...
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624 HW 6
1. Figure 9.32 shows the ACFs for 36 random numbers, 360 random numbers and 1,000 random numbers. a) Explain the differences among these figures. Do they all indicate that the data are white noise? Yes they all show that the data are white noise because all of the spikes on all 3 graphs fall within the dashed ACF plot. The main difference is the...
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DATA 624 HW 5
1) Consider the the number of pigs slaughtered in Victoria, available in the aus_livestock dataset. a) Use the ETS() function to estimate the equivalent model for simple exponential smoothing. Find the optimal values of alpha and l0 , and generate forecasts for the next four months. Optimal Values for alpha = 0.3579,l0 = 95487.5 avp<-aus_livesto...
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624-HW3
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) Since the trend of Australian population is steadily upward I will use a drift method in order to account for the forecast increase over time. aus <- global_economy%>% ...
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DATA 624 HW1
1) Use the help function to explore what the series gafa_stock, PBS, vic_elec and pelt represent. gafa_stock: Historical stock prices for Google, Amazon, Facebook and Apple in $USD from 2014-18. A time series tsibble containing data for the opening price of the stock the highest trading price, lowest price, closing price, adjusted closing price ...
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624 HW 2
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? Qatar has the highest average GDP per capita in the data set. We can see via the second plot that Qatar’s GDP per capita was not very high earlier on in the dataset ...
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