Probability Density Functions for Prediction Using Normal and Exponential Distribution

When data are found to be realizations of a specific distribution, constructing the probability density function based on this distribution may not lead best prediction result. In study, numerical simulations conducted using that follow normal and we examine whether functions have shapes different from can yield larger log-likelihoods than in light future data. The results indicate fitting produces better perspective predictive ability. Similarly, set exponential shows predictions obtained when corresponding fitted is slightly distribution. These observations demonstrate form generates known, use another achieve more desirable standpoint prediction.