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当因变量具有高自相关时，最佳的预测方法是什么？

[英]What is the best prediction measure when the dependent variable has a high autocorrelation?

原文 2018-11-15 01:22:35 8 0 machine-learning/ regression/ measure

I am working on predicting a dependent variable on a panel data. 我正在预测面板数据上的因变量。

I need to choose the prediction measure however I have the following issues: 我需要选择预测指标，但是存在以下问题：

I am working with a panel data and therefore mixing time steps and different individuals 我正在使用面板数据，因此会混合时间步骤和不同的人
The dependent variable is highly autocorrelated (the dependent variable is a yearly measure that I shift on a monthly basis and therefore is highly autocorrelated and sometimes has the same value for a number of periods) 因变量是高度自相关的（因变量是我每月变动的年度度量，因此是高度自相关的，有时在多个期间具有相同的值）

I worked with the R-squared, however, I believe there is some perverse effect due to the previous points and looking for a correction of the measure. 我使用R平方进行处理，但是，我相信由于前面提到的要点和寻找该度量的更正，会产生一些反常的影响。

Thank you. 谢谢。

0 个解决方案

什么是机器学习准确性的最佳措施 - What is the best measure for ACCURACY in MACHINE LEARNING

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无论输入什么，TFLearn DNN都具有相同的预测 - TFLearn DNN has the same prediction no matter what the input it

测量机器学习模型是否过度拟合的正确方法是什么？ - What is the right way to measure if a machine learning model has overfit?

我应该选择什么作为价格预测的目标变量？ - What should I choose as a target variable for price prediction?

当测试值和预测值之间的差异如此接近时，为什么我的 MSE 如此之高？ - Why is my MSE so high when the difference between test and prediction values are so close?

为什么在使用glmnet模型时R中的`predict`会返回高维预测？ - Why does `predict` in R when using a glmnet model return a high dimensional prediction?

在 Tensorflow 中，当使用预测即 'print(prediction[0][0])' 时，[0][0] 实际引用的值是什么？ - In Tensorflow, when using a prediction i.e. 'print(prediction[0][0])', what are the values [0][0] actually referencing?

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相关问题 什么是机器学习准确性的最佳措施 - What is the best measure for ACCURACY in MACHINE LEARNING 当因变量的变化很小时，可以使用什么度量来定义模型性能？ - What metric to use to define model performance when the change in dependent variable is very small? 使用xgboost进行分类时如何获得置信区间或预测离散度的度量？ - How to obtain a confidence interval or a measure of prediction dispersion when using xgboost for classification? 对因变量进行对数转换后的回归RMSE - Regression RMSE when dependent variable is log transformed 无论输入什么，TFLearn DNN都具有相同的预测 - TFLearn DNN has the same prediction no matter what the input it 测量机器学习模型是否过度拟合的正确方法是什么？ - What is the right way to measure if a machine learning model has overfit? 我应该选择什么作为价格预测的目标变量？ - What should I choose as a target variable for price prediction? 当测试值和预测值之间的差异如此接近时，为什么我的 MSE 如此之高？ - Why is my MSE so high when the difference between test and prediction values are so close? 为什么在使用glmnet模型时R中的`predict`会返回高维预测？ - Why does `predict` in R when using a glmnet model return a high dimensional prediction? 在 Tensorflow 中，当使用预测即 'print(prediction[0][0])' 时，[0][0] 实际引用的值是什么？ - In Tensorflow, when using a prediction i.e. 'print(prediction[0][0])', what are the values [0][0] actually referencing?

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当因变量具有高自相关时，最佳的预测方法是什么？

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