Triangle Notation | Triangle Probability Density Funciton (PDF) | Triangle Cumulative Distribution Function (CDF) | Triangle Mean | Triangle Variance | Method of Moments Estimation | Type 1 | Type 2 | Maximum Likelihood Estimation | Maximizing the Likelihood with respect to $c$ (given $a$ and $b$) | Case 1: $c$ is between the first and second to last order statistic $r \ \epsilon \ (1, \dots, n-1)$ | Side note on $z=c^r(1-c)^{n-r}$ being unimodal | Case 2: $c$ is between 0 and the first order statistic $r = 0$ | Case 3: $c$ is between the last order statistic $r = n$ and 1 | All Cases | Negative Log Likelihood | Case 1: $a = c \lt b$ | Case 2: $a \lt c = b$ | Case 3: $a \lt c \lt b$ | Gradient of the negative Log Likelihood Given $c$: | Hessian of the negative Log Likelihood Given $c$: | MLE Variance - Covariance | $r^{th}$ order statistic | Expected value of the $r^{th}$ order statistic | Expected Value of $r^{th}$ order statistic squared | Variance of the $r^{th}$ order statistic | Numerical Stability of Variance and Expected value of $r^{th}$ order statistic | Logarithmic Triangle distribution

Example 1: Simple Correlation | Example 2: Dirichlet distribution | Method 1: correlatedLHS | Method 2: q_dirichlet | Example 3: Rejection Sample

Question 1 | Answer | Question 2 | Question 3 | Question 5 | Question 6

Overview | Data Sets | Tornado Plot Examples | LM | type = "PercentChange" | type = "rangess" | type = "percentiles" | Including Categorical Variables | Changing Variable Names | Plotting Options | Extending the ggplot | GLM | Censored Data | Surival Regression or Accelerated Failure | Cox Proportional Hazards | Ridge Regression and LASSO | Machine Learning Models | Regression | Classification | Importance Plots | Linear Models | Using a dictionary to translate the variable names and chaning colors | Generalized Linear Models | Machine Learning

Theory of Latin Hypercube Sampling | Create a Simple LHS | Optimizing the Design | Method | Min Distance btwn pts | Mean Distance btwn pts | Max Correlation btwn pts:-----|:-----:|:-----:|:-----:randomLHS | r min(dist(A)) | r mean(dist(A)) | r max(abs(cor(A)-diag(10)))optimumLHS | r min(dist(A1)) | r mean(dist(A1)) | r max(abs(cor(A1)-diag(10)))maximinLHS | r min(dist(A2)) | r mean(dist(A2)) | r max(abs(cor(A2)-diag(10)))improvedLHS | r min(dist(A3)) | r mean(dist(A3)) | r max(abs(cor(A3)-diag(10)))geneticLHS (S) | r min(dist(A4)) | r mean(dist(A4)) | r max(abs(cor(A4)-diag(10)))geneticLHS (Maximin) | r min(dist(A5)) | r mean(dist(A5)) | r max(abs(cor(A5)-diag(10)))