quasi-monte carlo method 中文意思是什麼
quasi-monte carlo method
解釋
擬蒙特卡羅法-
The standard rejection sampling method which is introduced in chapter 2 is closely related to the problem of quasi - monte carlo integration of characteristic functions, whose accuracy may be lost due to the discontinuity of the characteristic functions
第2章介紹的標準拒絕抽樣方法其實跟特徵函數的蒙特卡羅積分有密切的關系。而由於特徵函數的不連續性,蒙特卡羅積分應有的誤差精度就達不到,拒絕抽樣的效果也就受到影響。 -
By comparing these two methods, we show the advantages of quasi - monte carlo method. we also introduce the standard monte carlo random search for optimization. the last but not least application is metropolis algorithms which is the origin of monte carlo method
第1章介紹了蒙特卡羅和擬蒙特卡羅積分的誤差估計並闡述了擬蒙特卡羅方法的優勢,同時介紹了擬蒙特卡羅的標準優化方法,最後介紹了蒙特卡羅方法的起源? metropolis模擬方法。 -
We apply the b - spline smoothed rejection sampling method to importance sampling. numerical experiments show that the error size o ( n - 1 ) is regained by using the b - spline smoothed rejection method for quasi - monte carlo estimate. the error bound of monte carlo method using b - spline smoothed importance sampling is also better than that of the standard monte carlo method
將b樣條光滑拒絕方法用於重要抽樣估計,數值例子顯示擬蒙特卡羅積分的精度重新達到了o ( n ~ ( - 1 ) )的階,而對于蒙特卡羅積分,採用b樣條光滑重要抽樣,其精度也比標準積分的精度o ( n ~ ( - 2 / 1 ) )好。
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