Long-term prediction of precipitation and hydrologic extremes with nonstationary oscillation processes

the effects of keyword and context methods on pronunciation and receptive/ productive vocabulary of low-intermediate iranian efl learners: short-term and long-term memory in focus

از گذشته تا کنون، تحقیقات بسیاری صورت گرفته است که همگی به گونه ای بر مثمر ثمر بودن استفاده از استراتژی های یادگیری لغت در یک زبان بیگانه اذعان داشته اند. این تحقیق به بررسی تاثیر دو روش مختلف آموزش واژگان انگلیسی (کلیدی و بافتی) بر تلفظ و دانش لغوی فراگیران ایرانی زیر متوسط زبان انگلیسی و بر ماندگاری آن در حافظه می پردازد. به این منظور، تعداد شصت نفر از زبان آموزان ایرانی هشت تا چهارده ساله با...

Terrestrial Sediment Yield Projection under the Bias-Corrected Nonstationary Scenarios with Hydrologic Extremes

For reliable prediction of sediment yield in a watershed, fine-scale projections for hydro-climate components were first obtained using the statistical bias correction and downscaling scheme based on the combination of an Artificial Neural Network (ANN), Nonstationary Quantile Mapping (NSQM) and Stochastic Typhoon Synthesis (STS) sub-modules. Successively, the hydrologic runoff and sediment yie...

Modeling and Prediction of Nonstationary Spatial Processes

Linear interpolation of random processes and extremes of a sequence of Gaussian nonstationary processes

We consider the limit distribution of maxima for a sequence of Gaussian nonstationary processes. As an application we investigate the linear interpolation error for a.s. continuous and mean square diierentiable Gaussian processes with stationary increments. The relation between the smoothness of incremental variance function, d(t) = E(X(s + t) ? X(s)) 2 ], and the interpolation errors in mean s...

Nonparametric prediction of nonstationary spatio-temporal processes

In spatial statistics often the response variable at a given location and time is observed together with some covariates which are known to influence the response. In several applications the relationship between the response and covariates may be unknown, and to prevent misspecification of the model, a nonparametric approach could be appropriate. In this paper prediction and forecasting of the...