Title Prediction Intervals for Three Basic Statistical Models
نویسنده
چکیده
منابع مشابه
Prediction of Climate Change in Western of Iran using Downscaling of HadCM3 Model under Different Scenarios
Abstract Considering that water resources are at risk from climate change, the study of temperature and precipitation changes in the coming years can lead to droughts such as droughts, sudden floods, high evaporation and environmental degradation. To this end, global climate models (GCMs) are designed to assess climate change. The outputs of these models have low spatial accuracy. In order ...
متن کاملNon-linear Bayesian prediction of generalized order statistics for liftime models
In this paper, we obtain Bayesian prediction intervals as well as Bayes predictive estimators under square error loss for generalized order statistics when the distribution of the underlying population belongs to a family which includes several important distributions.
متن کاملBayesian Prediction Intervals for Future Order Statistics from the Generalized Exponential Distribution
Let X1, X2, ..., Xr be the first r order statistics from a sample of size n from the generalized exponential distribution with shape parameter θ. In this paper, we consider a Bayesian approach to predicting future order statistics based on the observed ordered data. The predictive densities are obtained and used to determine prediction intervals for unobserved order statistics for one-sample ...
متن کاملThermal conductivity of Water-based nanofluids: Prediction and comparison of models using machine learning
Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...
متن کاملThermal conductivity of Water-based nanofluids: Prediction and comparison of models using machine learning
Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013