lm returns an object of class "lm" or for multiple responses of class c("mlm", "lm"). The functions summary and anova are used to obtain and print a summary and analysis of variance table of the results. The generic accessor functions coefficients, effects, fitted.values and residuals extract various useful features of the value returned by lm.

2021年7月27日 · The lm() function in R is used to fit linear regression models. This function uses the following basic syntax: lm(formula, data, …) where: formula: The formula for the linear model (e.g. y ~ x1 + x2) data: The name of the data frame that contains the data; The following example shows how to use this function in R to do the following:

R语言中的 lm()函数用于拟合线性模型，广泛应用于统计分析中，特别是在回归分析中。 这个函数可以让你探索两个或多个变量之间的关系，比如一个变量如何影响另一个变量。

2021年12月19日 · To fit a linear model in the R Language by using the lm() function, We first use data.frame() function to create a sample data frame that contains values that have to be fitted on a linear model using regression function. Then we use the lm() function to fit a certain function to a given data frame.

2024年7月29日 · Learn linear regression, a statistical model that analyzes the relationship between variables. Follow our step-by-step guide to learn the lm() function in R.

2018年7月9日 · R语言中的lm函数用于拟合线性回归模型，其基本语法为： lm(formula, data, subset, weights, na.action, method = "qr", model = TRUE, x = FALSE, y = FALSE, qr = TRUE, singular.ok = TRUE, contrasts = NULL, offset, ...)

2022年11月21日 · To use the method of least squares to fit a regression line in R, we can use the lm() function. This function uses the following basic syntax: model <- lm(response ~ predictor, data=df)

lm is used to fit linear models, including multivariate ones. It can be used to carry out regression, single stratum analysis of variance and analysis of covariance (although aov may provide a more convenient interface for these). method = "qr", model = TRUE, x = FALSE, y = FALSE, qr = TRUE, singular.ok = TRUE, contrasts = NULL, offset, ...)

2022年6月14日 · In this tutorial, we will learn how to perform a simple linear regression in R using lm() function. Simple Linear regression is one of the popular and common statistical methods that is used to understand the relationship between two numerical or quantitative variables, like height and weight of humans, age and height, years of education and ...

2023年2月17日 · Once we’ve fit a model, we can then use the predict () function to predict the response value of a new observation. This function uses the following syntax: predict (object, newdata, type=”response”) where: type: The type of prediction to make.