adding more resources

MSO202/Site.html

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+<a href="https://sites.google.com/view/mso202a/home"> Click Here</a>

MTH208/Assignments/assign1_sol (1).R

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+
+################ my code ############
+my.tennis <- function(p)
+{
+
+  # will track number of wins for A and B
+  A <- 0
+  B <- 0
+  for(k in 1:5)
+  {
+    next.game <- sample(0:1, size = 1, prob = c(p, 1-p))
+    if(next.game == 0) B <- B+1
+    if(next.game == 1) A <- A+1
+
+    # best-of-series finishes when any team reaches 3
+    if(A == 3 || B == 3)
+    {
+      x <- k 
+      break
+    }
+  }  
+  return(x)
+}
+
+
+my.matches <- numeric(length = 1e3)
+for(i in 1:1e3)
+{
+	my.matches[i] <- my.tennis(.7)
+}
+
+ans <- mean(my.matches)
+ans
+
+###################################

MTH208/Assignments/assign2_sol (2).R

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+
+################ my code ############
+my.prop.color <- function(img, col)
+{
+  col.mat <- as.array(img[,,1,])
+  dims <- dim(col.mat)
+
+  dist <- matrix(0, nrow = dims[1], ncol = dims[2])
+  for(i in 1:dims[1])
+  {
+    for(j in 1:dims[2])
+    {
+      dist[i,j] <- norm(col.mat[i,j, ] - col, "2")
+    }
+  }
+
+  props <- sum(dist < .5)/(dims[1]*dims[2])
+  return(props)
+}
+
+###################################

MTH208/Assignments/assign3_sol.R

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+
+library(rvest)
+html <- read_html("https://www.icc-cricket.com/rankings/womens/player-rankings/odi/batting")
+
+# Get the whole data as a table
+# First element in the list
+tab <- html_table(html)[[1]]
+
+# Replace first column with 1:100
+tab$Pos <- 1:100
+
+# Remove last column
+tab <- tab[, -5]
+
+# convert to data.frame
+# this step is not very necessary
+MY_icc_rank <- as.data.frame(tab) 
+

MTH208/Assignments/assign4_sol.R

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+library(rvest)
+
+html <- read_html("https://prsindia.org/covid-19/cases")
+
+foo <- html %>% html_table()
+foo <- foo[[1]]
+
+MY_india_rates <- foo[-1, ]
+MY_india_rates <- MY_india_rates[ ,-1]
+MY_india_rates <- as.data.frame(MY_india_rates)
+
+save(MY_india_rates, file = "covid.Rdata")
+

MTH208/Assignments/assign5_sol.R

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+
+my.func2 <- function(vec)
+{
+	temp <- log(vec)
+	return(temp/sum(temp))
+}

MTH208/Assignments/assign6_sol.cp

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+// cope and paste your code here.
+
+#include <Rcpp.h>
+using namespace Rcpp;
+
+
+// [[Rcpp::export]]
+NumericMatrix my_divideC(NumericMatrix x, NumericMatrix y) {
+  int n = x.nrow();
+  int m = x.ncol();
+
+  NumericMatrix out(n,m);
+
+  for(int i = 0; i < n; i++)
+  {
+    for(int j = 0; j < m; j++)
+    {
+      out(i,j) = x(i,j) / y(i,j); 
+    }
+  }
+  return out;
+}

MTH208/Assignments/assign7_sol.R

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+### Solution to assignment 7
+
+dat <- read.csv("data.csv")
+dat$X1 <- as.factor(dat$X1)
+dat$X2 <- as.factor(dat$X2)
+dat$X3 <- as.factor(dat$X3)
+
+## X2 is the variable that separates Var1 and Var2
+## into 3 visible groups
+
+plot(dat$Var1, dat$Var2, col = dat$X2, 
+  xlab = "Variable 1", ylab = "Variable 2", 
+  main = "Simpson's Paradox with X2", pch = 16)
+for(i in 1:length(levels(dat$X2)))
+{
+  foo <- subset(dat, dat$X2 == levels(dat$X2)[i])
+  abline(lm(foo$Var2 ~ foo$Var1), col = i)
+}
+legend("topleft", legend = levels(dat$X2), 
+  title = "X2", fill = 1:3)

MTH208/EndSem/Cans2.cpp

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+#include <Rcpp.h>
+using namespace Rcpp;
+
+
+// [[Rcpp::export]]
+NumericVector sumsC(NumericMatrix x, int s)
+{
+  // Declaring the output vector
+  NumericVector colSum(s);
+
+  // Filling the output vector with zeros
+  for (int i = 0; i < s; i++)
+  {
+    colSum[i] = 0;
+  }
+
+  // Calculating the column sums
+  for (int i = 0; i < x.nrow(); i++)
+  {
+    for (int j = 0; j < s; j++)
+    {
+      colSum[j] = colSum[j] + x(i, j);
+    }
+  }
+
+  return colSum;
+}

MTH208/EndSem/README.md

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+Answers are of a student, not the professor's.

MTH208/EndSem/ans1.R

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+autoreg_fast <- function(n, rho)
+{
+  # Allocating space to the out vector beforehand
+  out <- numeric(length = n)
+
+  # A slight improvement was observed when calculating
+  # the random values at once
+  errors <- rnorm(n - 1)
+
+  # Doing the required calculations
+  out[1] <- 0
+  for(t in 2:n)
+  {
+    error <- errors[t-1]
+    error <- rho*out[t-1] + error
+    out[t] <- error
+  }
+
+  return(out)
+}

MTH208/EndSem/ans2.R

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+library(Rcpp)
+
+sourceCpp(file = "Cans2.cpp")
+
+sel_sums <- function(mat){
+  # Obtaining the size of the square matrix
+  p = dim(mat)[1]
+
+  # Randomly choosing a number s between 1 and p (inclusive)
+  s = sample(1:p, size = 1)
+
+  # Calling the sourced C++ function
+  return(sumsC(mat, s))
+}

MTH208/EndSem/ans3.R

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+load("ques3.Rdata")
+
+# Size of the square matrix
+p <- dim(mat)[1]
+
+# Eigenvalues of the matrix
+eigen.values <- eigen(mat, only.values = TRUE)$values
+
+# Declaring the log of the answer
+log.ans <- 0
+
+# Adding sum terms obtained on logarithm
+log.ans <- log.ans + (p * log(2.7)) - (p * log(p)) + sum(log(1:p))
+
+# Adding the logarithm of the determinant term
+log.ans <- log.ans + ((1/p) * sum(log(eigen.values)))
+
+# Adding (effectively subtracting) the logarithm of the trace term
+log.ans <- log.ans - log(sum(eigen.values))
+
+ans <- exp(log.ans)

MTH208/EndSem/ans4.R

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+library(MASS)
+library(tidyverse)
+
+# Calculating incidents per year of every ship
+dat <- ships %>%
+  select(type, service, incidents) %>%
+  filter(service != 0) %>%
+  mutate(`Incidents per Year` = (incidents / (service / 12)))
+
+# Creating boxplot of Incidents per year v/s Type of Ship
+plt <- ggplot(dat) +
+  geom_boxplot(
+    aes(x = type, y = `Incidents per Year`)
+  ) +
+  labs(
+    title = "Incidents per Year of different types of Ships"
+  ) +
+  xlab("Type of Ship")
+
+## This plot disproves the hypothesis.
+## The ships of type B were also used for most
+## number of months which had led to most number
+## of accidents. Ship type E had the most number
+## incidents per year.
+
+plt

MTH208/MidSem/README.md

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+Answers are of a student, not the professor's.

MTH208/MidSem/ans1.R

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+# 'n' is the number of people in the room
+# The function returns TRUE when 2 people share the same birthday
+birthday <- function (n){
+  # Getting the random birthdays of people in the room
+  bdates <- sample(1:365, size = n, replace = TRUE)
+
+  # Taking a vector containing unique birthdays
+  uniq_dates <- unique(bdates)
+
+  # Checking whether all birthdays are unique or not
+  if (length(bdates) != length(uniq_dates)){
+    return(TRUE)
+  } else {
+    return(FALSE)
+  }
+}
+
+outcomes25 <- replicate(1000, birthday(25))
+ans25 <- length(outcomes25[outcomes25]) / 1000
+
+outcomes50 <- replicate(1000, birthday(50))
+ans50 <- length(outcomes50[outcomes50]) / 1000

MTH208/MidSem/ans2.R

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+library(imager)
+
+# An imager image is taken as input
+flip <- function (img){
+  # Convert the image pixel and color values into an array
+  orig.img.arr <- as.array(img[, , 1, ])
+
+  # Create an empty array to contain values of new image
+  new.img.arr <- array(0, dim = dim(orig.img.arr))
+
+  # The following loop fills the new image array
+  img.dims <- dim(orig.img.arr)
+  for (i in 1:img.dims[1]){
+    for (j in 1:img.dims[2]){
+      for (k in 1:img.dims[3]){
+        new.img.arr[i, j, k] <- orig.img.arr[img.dims[1] + 1 - i, j, k]
+      }
+    }
+  }
+
+  # Create an imager image from the array and return it
+  new.img <- as.cimg(new.img.arr)
+  return(new.img)
+}

MTH208/MidSem/ans3.R

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+library(tibble)
+library(tidyverse)
+
+# Read the titanic data from the csv file
+titanic.data <- as_tibble(read_csv("titanic.csv"))
+
+# Convert the Survived column into a factor having the values "Died" and "Survived"
+titanic.data$Survived <- factor(titanic.data$Survived)
+levels(titanic.data$Survived) <- c("Died", "Survived")
+
+# The final graph
+finalP <- ggplot(titanic.data, aes(x = Survived, y = Fare)) +
+  geom_boxplot(aes(color = Sex)) +
+  labs(title = "Fare vs Survival",
+       subtitle = "Irrespective of Sex, richer people survived",
+       x = "",
+       y = "Fare"
+  ) +
+  coord_flip()