Publications by Mohamed Hassan-El Serafi
Data 624 Homework 6
library(tidyverse) library(fpp3) ## Warning: package 'tsibble' was built under R version 4.2.3 library(tseries) library(forecast) library(kableExtra) library(reactable) library(seasonal) library(tsibble) 1. Figure 9.32 shows the ACFs for 36 random numbers, 360 random numbers and 1,000 random numbers. knitr::include_graphics("/Users/mohamedhassan/D...
10024 sym R (14457 sym/154 pcs) 61 img
Data 624 Homework 5
library(fpp3) library(tidyverse) library(forecast) library(kableExtra) library(reactable) options(scipen = 999) set.seed(123456) 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...
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Data 624 Homework 4
library(tidyverse) library(mlbench) library(kableExtra) library(reactable) library(GGally) library(caret) library(e1071) library(univOutl) library(moments) library(outliers) library(cowplot) library(mice) library(VIM) 3.1 The UC Irvine Machine Learning Repository6 contains a data set related to glass identification. The data consist of 214 glass s...
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Data 624 Homework 3
library(fpp3) library(tidyverse) library(kableExtra) library(seasonal) library(reactable) library(tsibble) options(scipen=100) 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) data("global_economy") global_economy |> s...
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Data 624 Homework 2
library(fpp3) library(tidyverse) library(kableExtra) library(reactable) library(seasonal) library(tsibble) 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? data("global_economy") gdp_per_capita <- global_economy |> ...
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Data 624 Homework 1
1. Explore the following four time series: Bricks from aus_production, Lynx from pelt, Close from gafa_stock, Demand from vic_elec. Loading Libaries: library(fpp3) library(tidyverse) library(reactable) library(tsibble) library(kableExtra) Loading Datasets: data("aus_production") data("pelt") data("gafa_stock") data("vic_elec") Use ? (or help()) to...
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Data 605 Final Exam/Project
library(reactable) library(vtable) library(caret) library(GGally) library(tidyverse) library(plotly) library(LaplacesDemon) library(ggeasy) library(corrplot) library(matrixcalc) library(Matrix) library(MASS) library(moments) library(car) Problem 1. Using R, set a random seed equal to 1234 (i.e., set.seed(1234)). Generate a random variable X that h...
12075 sym R (18858 sym/160 pcs) 48 img 1 tbl
Data 605 Final Exam/Project
library(reactable) library(vtable) library(caret) library(GGally) library(tidyverse) library(plotly) library(LaplacesDemon) library(ggeasy) library(corrplot) library(matrixcalc) library(Matrix) library(MASS) library(moments) library(car) Problem 1. Using R, set a random seed equal to 1234 (i.e., set.seed(1234)). Generate a random variable X that h...
12145 sym R (18831 sym/159 pcs) 48 img 1 tbl
Data 605 HW15
1. Find the equation of the regression line for the given points. Round any final values to the nearest hundredth, if necessary. \(( 5.6, 8.8 ), ( 6.3, 12.4 ), ( 7, 14.8 ), ( 7.7, 18.2 ), ( 8.4, 20.8 )\) library(tidyverse) x <- c(5.6, 6.3, 7, 7.7, 8.4) y <- c(8.8, 12.4, 14.8, 18.2, 20.8) df <- as.data.frame(x, y) # Rounding values to the nearest hu...
4043 sym R (560 sym/8 pcs)
Data 605 HW14
This week, we’ll work out some Taylor Series expansions of popular functions. For each function, only consider its valid ranges as indicated in the notes when you are computing the Taylor Series expansion. Please submit your assignment as an R-Markdown document. Taylor Series is defined as \(f(x) = \sum\limits_{n=0}^{\infty}\frac{f^{(n)}(c)}{n!}(...
2717 sym R (772 sym/9 pcs)