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diff --git a/Probability/Gamblers_Ruin.Rmd b/Probability/Gamblers_Ruin.Rmd
@@ -0,0 +1,149 @@
+---
+title: "Gambler's Ruin"
+subtitle: Simulations with R
+author: DragonflyStats.github.io
+output:
+  prettydoc::html_pretty:
+    theme: cayman
+    highlight: github
+---
+
+
+\section{Gambler's Ruin}
+
+Consider a gambler who starts with an initial fortune of \$1 and then on each successive gamble
+either wins \$1 or loses \$1 independent of the past with probabilities p and q = 1-p respectively.
+
+Suppose the gambler has a starting kitty of A.
+This gamblers places bets with the “Banker”, who has an initial fortune B. We will look at the game from the perspective of the gambler only.
+The Banker is, by convention, the richer of the two.
+
+\begin{itemize}
+\item Probability of successful gamble for gambler : p
+\item Probability of unsuccessful gamble for gambler : q 	(where q =  1 - p )
+\item Ratio of success probability to failure success:	$s = p / q$
+\item Conventionally the game is biased in favour of the Banker (i.e. $q>p$ and $s<1$)
+\end{itemize}
+
+Let $R_n$ denote the Gambler’s total fortune after the $n-$th gamble.
+
+If the Gambler wins the first game, his wealth becomes $R_n =A+1$.
+If he loses the first gamble, his wealth becomes $R_n = A-1$.
+The entire sum of money at stake is the “Jackpot” i.e.   $A+B$.
+The game ends when the Gambler wins the Jackpot ($R_n = A+B$) or loses everything ($R_n = 0$).
+
+
+### Simulation a Single Gamble}
+
+
+To simulate one single bet, compute a single random number between 0 and 1.
+```{r}
+
+runif(1)
+```
+
+
+Lets assume that the game is biased in favour of the Banker
+p = 0.45 , q = 0.55.
+If the number is less than 0.45, the gamble wins. Otherwise the Banker wins.
+
+
+> runif(1)
+[1] 0.1251274
+>#Gambler Loses
+>
+> runif(1)
+[1] 0.754075
+>#Gambler wins
+>
+> runif(1)
+[1] 0.2132148
+>#Gambler Loses
+>
+> runif(1)
+[1] 0.8306269
+```
+
+%----------------------------------------------------------------------%
+\newpage
+Let A be the Gambler's Kitty at the start of the gambling.
+Let B be the Banker's Wealth.
+The probability of A winning a gamble is p.
+The vector $R_n$ records the gambler's worth on an ongoing basis. At the start, The first value is A.
+```{r}
+
+
+A=20;B=100;p=0.47
+Rn=c(A)
+
+probval = runif(1)
+
+if (probval < p)
+ {
+ A = A+1; B =B-1
+ }else{A=A-1;B=B+1}
+
+#Save the values from each bet
+Rn=c(Rn,A)
+```
+
+\newpage
+Should the Gambler win the entire jackpot (A+B). The game would also cease. We include a \textbf{\texttt{break}} statement to stop the loop if the gambler wins the entire jackpot. A break statement will stop a loop if a certain logical condition is met.
+
+```{r}
+
+A=20;B=100;p=0.47
+Rn=c(A)
+Total=A+B
+
+while(A>0)
+  {
+  UnifVal=runif(1)
+
+  if(UnifVal <= p)
+     {
+     A = A+1; B =B-1
+     }else{A=A-1;B=B+1}
+  Rn=c(Rn,A)
+  if(A==Total){break}
+  }
+```
+
+We can construct a plot to depict the gambler's ongoing fortunes in the game. We use a \texttt{for} loop, that implements the game, recording the duration of the game each time. The duration of each game is the dimension of the \texttt{Rn} vector, i.e. \texttt{length(Rn)}.
+
+
+```{r}
+
+A.ini=20;B=100;p=0.47
+M=1000
+RnDist=numeric()
+Total=A+B
+
+for (i in 1:M)
+    {
+    Rn=numeric()
+    Rn[1]=A
+    A=A.ini
+    while(A>0)
+        {
+       
+        UnifVal=runif(1)
+
+        if(UnifVal <= p)
+            {
+            A = A+1; B =B-1
+            }else{A=A-1;B=B+1}
+        Rn=c(Rn,A)
+        if(A==Total){break}
+        }
+    RnDist=c(RnDist,length(Rn))
+    }
+    
+
+```
+
+### Distribution of Durations}
+We can use for loop to get a sense of the duration (i.e. the number of rounds a game will last).
+\newpage
+\end{document}
+
diff --git a/Probability/Gamblers_Ruin.html b/Probability/Gamblers_Ruin.html
diff --git a/Probability/PREPAREA/Gamblers Ruin.Rmd → Probability/PREPAREA/Monty_Hall_Problem.Rmd b/Probability/PREPAREA/Gamblers Ruin.Rmd → Probability/PREPAREA/Monty_Hall_Problem.Rmd
@@ -1,9 +1,11 @@
 ---
-title: "Untitled"
+title: "The Monty Hall Problem"
+susbtitl: Simulations with R
+author: DragonflyStats.github.io
 output:
-  html_document:
-    toc: true
-    fig_caption: true
+  prettydoc::html_pretty:
+    theme: cayman
+    highlight: github
 ---
 
 
@@ -208,143 +210,3 @@ The output of this program would look like this. The proportion is approximately
 > SwitchCount
 [1] 677
 ```
-
-%---------------------------------------------------------------%
-\section{Gambler's Ruin}
-
-Consider a gambler who starts with an initial fortune of \$1 and then on each successive gamble
-either wins \$1 or loses \$1 independent of the past with probabilities p and q = 1-p respectively.
-
-Suppose the gambler has a starting kitty of A.
-This gamblers places bets with the “Banker”, who has an initial fortune B. We will look at the game from the perspective of the gambler only.
-The Banker is, by convention, the richer of the two.
-
-\begin{itemize}
-\item Probability of successful gamble for gambler : p
-\item Probability of unsuccessful gamble for gambler : q 	(where q =  1 - p )
-\item Ratio of success probability to failure success:	$s = p / q$
-\item Conventionally the game is biased in favour of the Banker (i.e. $q>p$ and $s<1$)
-\end{itemize}
-
-Let $R_n$ denote the Gambler’s total fortune after the $n-$th gamble.
-
-If the Gambler wins the first game, his wealth becomes $R_n =A+1$.
-If he loses the first gamble, his wealth becomes $R_n = A-1$.
-The entire sum of money at stake is the “Jackpot” i.e.   $A+B$.
-The game ends when the Gambler wins the Jackpot ($R_n = A+B$) or loses everything ($R_n = 0$).
-
-
-### Simulation a Single Gamble}
-
-
-To simulate one single bet, compute a single random number between 0 and 1.
-```{r}
-
-runif(1)
-```
-
-
-Lets assume that the game is biased in favour of the Banker
-p = 0.45 , q = 0.55.
-If the number is less than 0.45, the gamble wins. Otherwise the Banker wins.
-
-
-> runif(1)
-[1] 0.1251274
->#Gambler Loses
->
-> runif(1)
-[1] 0.754075
->#Gambler wins
->
-> runif(1)
-[1] 0.2132148
->#Gambler Loses
->
-> runif(1)
-[1] 0.8306269
-```
-
-%----------------------------------------------------------------------%
-\newpage
-Let A be the Gambler's Kitty at the start of the gambling.
-Let B be the Banker's Wealth.
-The probability of A winning a gamble is p.
-The vector $R_n$ records the gambler's worth on an ongoing basis. At the start, The first value is A.
-```{r}
-
-
-A=20;B=100;p=0.47
-Rn=c(A)
-
-probval = runif(1)
-
-if (probval < p)
- {
- A = A+1; B =B-1
- }else{A=A-1;B=B+1}
-
-#Save the values from each bet
-Rn=c(Rn,A)
-```
-
-\newpage
-Should the Gambler win the entire jackpot (A+B). The game would also cease. We include a \textbf{\texttt{break}} statement to stop the loop if the gambler wins the entire jackpot. A break statement will stop a loop if a certain logical condition is met.
-
-```{r}
-
-A=20;B=100;p=0.47
-Rn=c(A)
-Total=A+B
-
-while(A>0)
-  {
-  UnifVal=runif(1)
-
-  if(UnifVal <= p)
-     {
-     A = A+1; B =B-1
-     }else{A=A-1;B=B+1}
-  Rn=c(Rn,A)
-  if(A==Total){break}
-  }
-```
-
-We can construct a plot to depict the gambler's ongoing fortunes in the game. We use a \texttt{for} loop, that implements the game, recording the duration of the game each time. The duration of each game is the dimension of the \texttt{Rn} vector, i.e. \texttt{length(Rn)}.
-
-
-```{r}
-
-A.ini=20;B=100;p=0.47
-M=1000
-RnDist=numeric()
-Total=A+B
-
-for (i in 1:M)
-    {
-    Rn=numeric()
-    Rn[1]=A
-    A=A.ini
-    while(A>0)
-        {
-       
-        UnifVal=runif(1)
-
-        if(UnifVal <= p)
-            {
-            A = A+1; B =B-1
-            }else{A=A-1;B=B+1}
-        Rn=c(Rn,A)
-        if(A==Total){break}
-        }
-    RnDist=c(RnDist,length(Rn))
-    }
-    
-
-```
-
-### Distribution of Durations}
-We can use for loop to get a sense of the duration (i.e. the number of rounds a game will last).
-\newpage
-\end{document}
-
diff --git a/Probability/PREPAREA/Monty_Hall_Problem.html b/Probability/PREPAREA/Monty_Hall_Problem.html
diff --git a/Probability/PREPAREA/rsconnect/documents/Monty_Hall_Problem.Rmd/rpubs.com/rpubs/Document.dcf b/Probability/PREPAREA/rsconnect/documents/Monty_Hall_Problem.Rmd/rpubs.com/rpubs/Document.dcf
@@ -0,0 +1,11 @@
+name: Document
+title:
+username:
+account: rpubs
+server: rpubs.com
+hostUrl: rpubs.com
+appId: https://api.rpubs.com/api/v1/document/1104051/9fc3555f99504a54b62bbc8adaf7d53b
+bundleId: https://api.rpubs.com/api/v1/document/1104051/9fc3555f99504a54b62bbc8adaf7d53b
+url: http://rpubs.com/publish/claim/1104051/ca2a8a184dd94c818f5a6e64654bf1e2
+when: 1698175835.74178
+lastSyncTime: 1698175835.74178
diff --git a/Statistics/01-ModellingCountVariables/22-Fishing-ZeroInflatedPoisson.Rmd b/Statistics/01-ModellingCountVariables/22-Fishing-ZeroInflatedPoisson.Rmd
@@ -1,8 +1,15 @@
 ---
 title: "Poisson Regression - Zero-Inflated Poisson regression"
-output: html_document
+susbtitl: The {vcd} R Package
+author: DragonflyStats.github.io
+output:
+  prettydoc::html_pretty:
+    theme: cayman
+    highlight: github
 ---
 
+
+
 ```{r setup, include=FALSE}
 knitr::opts_chunk$set(echo = TRUE)
 library(knitr)
@@ -33,30 +40,12 @@ head(fishing)
 ```
 
 
-<table>
-<thead><tr><th>X</th><th>nofish</th><th>livebait</th><th>camper</th><th>persons</th><th>child</th><th>xb</th><th>zg</th><th>count</th></tr></thead>
-<tbody>
-	<tr><td>1         </td><td>1         </td><td>0         </td><td>0         </td><td>1         </td><td>0         </td><td>-0.8963146</td><td> 3.0504048</td><td>0         </td></tr>
-	<tr><td>2         </td><td>0         </td><td>1         </td><td>1         </td><td>1         </td><td>0         </td><td>-0.5583450</td><td> 1.7461489</td><td>0         </td></tr>
-	<tr><td>3         </td><td>0         </td><td>1         </td><td>0         </td><td>1         </td><td>0         </td><td>-0.4017310</td><td> 0.2799389</td><td>0         </td></tr>
-	<tr><td>4         </td><td>0         </td><td>1         </td><td>1         </td><td>2         </td><td>1         </td><td>-0.9562981</td><td>-0.6015257</td><td>0         </td></tr>
-	<tr><td>5         </td><td>0         </td><td>1         </td><td>0         </td><td>1         </td><td>0         </td><td> 0.4368910</td><td> 0.5277091</td><td>1         </td></tr>
-	<tr><td>6         </td><td>0         </td><td>1         </td><td>1         </td><td>4         </td><td>2         </td><td> 1.3944855</td><td>-0.7075348</td><td>0         </td></tr>
-</tbody>
-</table>
-
-
-
 
 ```{r}
 ## histogram with x axis 
 ggplot(fishing, aes(count)) + geom_histogram()
 ```
 
-    `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
-
-
-
 
 
 
@@ -66,12 +55,6 @@ ggplot(fishing, aes(count)) + geom_histogram()
 ggplot(fishing, aes(count)) + geom_histogram() + scale_x_log10()
 ```
 
-    `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
-    Warning message:
-    "Removed 142 rows containing non-finite values (stat_bin)."
-
-
-
 
 ```{r}
 ## Run a Zero-Inflated Poisson Regression Analysis to predict number of fish caught

diff --git a/Statistics/01-ModellingCountVariables/22-Fishing-ZeroInflatedPoisson.html b/Statistics/01-ModellingCountVariables/22-Fishing-ZeroInflatedPoisson.html
diff --git a/...ables/rsconnect/documents/22-Fishing-ZeroInflatedPoisson.Rmd/rpubs.com/rpubs/Document.dcf b/...ables/rsconnect/documents/22-Fishing-ZeroInflatedPoisson.Rmd/rpubs.com/rpubs/Document.dcf
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