Category: R

How to Calculate SMAPE in R?, SMAPE indicates the symmetric mean absolute percentage error.SMAPE is mainly used to measure the predictive accuracy of models. Mathematical formula is SMAPE = (1/n) * Σ(|forecast – actual|...

Mean Absolute Error in R, when we do modeling always need to measure the accuracy of the model fit. The mean absolute error (MAE) allows us to measure the accuracy of a given model....

Heteroscedasticity in Regression, one of the easiest ways to measure heteroscedasticity is while using the Breusch-Pagan Test. The test is mainly used to identify if heteroscedasticity is present in a regression analysis. This tutorial...

Boxplots in R, A boxplot is a plot that displays the five-digit summary of a dataset. The five-digit summary is the lowest value, the first quartile, the median, the third quartile, and the maximum value. We can use a boxplot to easily visualize a set of data. Principal component analysis (PCA)...

Calculate Phi Coefficient in R, first, we need to understand what is Phi Coefficient? It is a measurement of the degree of association between two binary variables. When it’s coming to inference it is similar to the...

Root Mean Square Error In R, The root mean square error (RMSE) allows us to measure how far predicted values are from observed values in a regression analysis. In other words, how concentrated the...

ANCOVA in R, Analysis of covariance is used to measure the main effect and interaction effects of categorical variables on a continuous dependent variable while controlling the effects of selected other continuous variables which...

COUNTIF Function in R, As we know if we want to count the length of the vector we can make use of the length function. In case you want to count only the number...

Covariance Matrix in R, Covariance is a measure of the degree to which two variables are linearly associated. We can measure how changes in one variable are associated with another variable. A covariance matrix...