SARIMA(1,1,1)(2,1,2)[12]-GARCH(1,1)模型预测代码（R语言）不使用“rugarch”包

以下是SARIMA(1,1,1)(2,1,2)[12]-GARCH(1,1)模型的预测代码（R语言）：

# 导入数据
data <- read.csv("data.csv", header=TRUE, sep=",")

# 安装并导入相关包
library(forecast)
library(tseries)
library(stats)

# 拟合SARIMA模型
sarima_model <- arima(data, order=c(1,1,1), seasonal=list(order=c(2,1,2), period=12))

# 提取SARIMA模型残差
residuals <- sarima_model$residuals

# 拟合GARCH模型
garch_model <- garch(residuals, order=c(1,1))

# 预测未来12个时间点的值
forecast_horizon <- 12
sarima_garch_forecast <- numeric(forecast_horizon)
sarima_garch_forecast[1] <- sarima_model$coef[1] + sarima_model$coef[2] * data[length(data)] + sarima_model$coef[3] * sarima_model$residuals[length(residuals)] + sarima_model$coef[4] * sarima_model$residuals[length(residuals)-1] + sarima_model$coef[5] * sarima_model$residuals[length(residuals)-12] + sarima_model$coef[6] * sarima_model$residuals[length(residuals)-13] + garch_model@fit$omega
for (i in 2:forecast_horizon) {
  sarima_garch_forecast[i] <- sarima_model$coef[1] + sarima_model$coef[2] * sarima_garch_forecast[i-1] + sarima_model$coef[3] * sarima_model$residuals[length(residuals)-i+2] + sarima_model$coef[4] * sarima_model$residuals[length(residuals)-i+1] + sarima_model$coef[5] * sarima_model$residuals[length(residuals)-i+1-12] + sarima_model$coef[6] * sarima_model$residuals[length(residuals)-i+1-13] + garch_model@fit$omega + garch_model@fit$coef[1] * sarima_garch_forecast[i-1]^2 + garch_model@fit$coef[2] * sarima_garch_forecast[i-1]
}

# 输出预测结果
cat(paste("SARIMA-GARCH模型未来12个时间点预测值：\n"))
cat(sarima_garch_forecast)

请注意，这只是一个示例代码，需要根据实际情况进行调整和修改。