Use of Tilde ~ in R

In this article, we will be looking at the use of tilde(~) in the R programming language.

Tilde symbol l is used within formulas of statistical models, as mainly this symbol is used to define the relationship between the dependent variable and the independent variables in the statistical model formula in the R programming language. The left side of the tilde symbol specifies the target variable (dependent variable or outcome) and the right side of the tilde specifies the predictor variable(independent variables).

Using ~ within lm() Function to Estimate Linear Regression Model

In this, we will be going through the process of applying the linear regression fitting of the model and further by the use of the tilde symbol will be used inside the lm() function and at the left side of the tilde symbol specifies the target variable (dependent variable or outcome) and the right side of the tilde specifies the predictor variable(independent variables). The ~ symbol defines the predictors and the target variable when used with the lm function in the Rb programming language

lm() is used to fit linear models. It can be used to carry out regression, single stratum analysis of variance and analysis of covariance.

Syntax:

lm(formula, data, subset, weights, na.action,method = “qr”, model = TRUE, x = FALSE, y = FALSE, qr = TRUE, singular.ok = TRUE, contrasts = NULL, offset, …)

Parameters:

• formula:-an object of class “formula”: a symbolic description of the model to be fitted.
• data:-an optional data frame, list, or environment containing the variables in the model.
• subset:-an optional vector specifying a subset of observations to be used in the fitting process.
• weights:-an optional vector of weights to be used in the fitting process. Should be NULL or a numeric vector. If non-NULL, weighted least squares are used with weights.

Example: Program to show use of tilde sign

R

g1 <- rnorm(1000)
g2 <- rnorm(1000) + g1

o<-rnorm(1000) + g1 + g2

gfg <- data.frame(g1, g2, o)

model <- lm(o ~ g1 + g2,gfg)
summary(model)

Output:

Example 2: Program to show use of tilde sign

R

g1 <- rnorm(500)
g2 <- rnorm(500) * g1

o<-rnorm(500) + g1 - g2

gfg <- data.frame(g1, g2, o)

model <- lm(o ~ g1 + g2,gfg)
summary(model)

Output: