chatglm4 调用申请
    ## How to Use the chatglm4 Function.
    The `chatglm4` function in R is a powerful tool for fitting generalized linear models to data. It can be used to fit a variety of models, including logistic regression, Poisson regression, and negative binomial regression.
    The `chatglm4` function takes a number of arguments, including:
    `formula`: A formula specifying the model to be fit.
    `data`: A data frame containing the data to be used to fit the model.
    `family`: The family of the distribution of the response variable.
    `control`: A list of control parameters for the fitting process.
    ## Basic Example.
    The following code shows how to use the `chatglm4` function to fit a logistic regression model to data:
    # Load the necessary libraries.
    library(chatglm4)。
    library(ggplot2)。
    # Load the data.
    data <read.csv("data.csv")。
    # Fit the model.
    model <chatglm4(y ~ x, data = data, family = "binomial")。
    # Print the model summary.
    summary(model)。
    # Plot the model predictions.
    ggplot(data, aes(x, y)) +。
      geom_point() +。
      geom_line(aes(y = predict(model, newdata = data))) +。
      labs(title = "Logistic Regression Model",。
          x = "x",。
          y = "y")。
    ## Advanced Example.
    The `chatglm4` function can also be used to fit more complex models, such as models with multiple predictors or models with non-linear relationships between the predictors and the response variable.
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    The following code shows how to use the `chatglm4` function to fit a Poisson regression model with multiple predictors and a non-linear relationship between one of the predictors and the response variable: