Event-specific multiplicative cascade models and an application to rainfall

Mixtures of multiplicative cascade models in geochemistry

Multifractal modeling of geochemical map data can help to explain the nature of frequency distributions of element concentration values for small rock samples and their spatial covariance structure. Useful frequency distribution models are the lognormal and Pareto distributions which plot as straight lines on logarithmic probability and log-log paper, respectively. The model of de Wijs is a sim...

Downscaling Spatial Rainfall Field from Global Scale to Local Scale Using Improved Multiplicative Random Cascade Method

Synopsis Non-homogenous multiplicative random cascade method downscales spatial rainfall field from a coarse scale into a finer one. Currently, this kind of downscaling is less reliable even though it correctly produces a long term average spatial pattern. It fails reproducing the patterns in repeated trials; and there is a higher chance of magnitude fluctuation. These drawbacks are needed to o...

construction and validation of translation metacognitive strategy questionnaire and its application to translation quality

like any other learning activity, translation is a problem solving activity which involves executing parallel cognitive processes. the ability to think about these higher processes, plan, organize, monitor and evaluate the most influential executive cognitive processes is what flavell (1975) called “metacognition” which encompasses raising awareness of mental processes as well as using effectiv...

An Analysis Of Energy Consumption In Transportation And Industrial Sectors- A Multiplicative LMDI Approach With Application To Iran

Local generalised method of moments: an application to point process‐based rainfall models

Long series of simulated rainfall are required at point locations for a range of applications, including hydrological studies. Clustered point process-based rainfall models have been used for generating such simulations for many decades. These models suffer from a major limitation, however: their stationarity. Although seasonality can be allowed by fitting separate models for each calendar mont...