prediction interval coverage probability
时间: 2024-01-02 11:05:05 浏览: 26
Prediction interval coverage probability refers to the probability that a prediction interval will contain the true value of the dependent variable for a new observation. In other words, if we were to repeat the process of estimating a prediction interval for a new observation many times, the coverage probability would be the proportion of those intervals that actually contain the true value of the dependent variable. Ideally, the coverage probability should be close to the nominal level of the prediction interval, which is typically set at 95% or 99%. If the coverage probability is lower than the nominal level, it suggests that the prediction interval is too narrow and does not account for all sources of variability in the data. On the other hand, if the coverage probability is higher than the nominal level, it suggests that the prediction interval is too wide and may not be very useful for making predictions.
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