1)conditional cumulative distribute function条件概率分布函数 2)conditional probability function条件概率函数 3)Conditional probability distribution条件概率分布 1.And the marginal probability distribution functions and the conditional probability distribution functions about cost and schedule are formed by using regre...
The distribution function of the average density of the pits and the deepest pits may be set up by the statistico analysis. 为了得到蚀孔的统计规律,本文用柏松概率分布函数求得腐蚀活性点出现个数的规律,再用古比极值统计第一类近似函数求得最深腐蚀孔深度的概率分布,以此来评价材料的耐点蚀性能。 2. ...
Kernel type estimators for the conditional cumulative distribution function and the successive derivatives of the conditional density are introduced. Asymptotic properties are stated for each of these estimates, and they are applied to the estimations of the conditional mode and conditional quantiles. Our...
Specifically, the local linear estimators of the conditional cumulative distribution function and of the successive derivatives of the conditional density are constructed. Then, the asymptotic properties of these estimators, in terms of the almost-complete convergence with rates, are stated. Moreover, ...
These are the areas within an interval below the conditional probability density function. Adding these areas for each cutoff reproduces the cumulative probabilities. Successive Cokriging of Indicators Having the cross-covariances, the successive cokriging of indicators approach proceeds as an extension of...
A CDF query is a type of statistical query that allows you to find the conditional cumulative distribution function (CDF) of a variable given a specific condition or set of conditions. It is used to analyze the relationship between variables and determine the probability of a certain outcome occ...
The exposure variable U is obtained from the cumulative distribution function of t(3) distribution. The error term follows student’s t distribution with three degrees of freedom. In both scenarios, we set n=200 and p=1000. The covariance matrix is defined as Σ=(ρ|i−j|)(p+1)×(p...
So we write the cumulative distribution function (CDF) forRtRtas: FRt|θ(rt|θ)=Pr(Rt<rt|θ)FRt|θ(rt|θ)=Pr(Rt<rt|θ) NowRtRt, givenθθis a 1-to-1 function ofZtZt. Now we substitute this relationRt=μt(θ)+ht(θ)−−−−√ZtRt=μt(θ)+ht(θ)Ztand re-arrange ...
In addition to these aforementioned peak-amplitude-based IMs, Table 4.1 also illustrates that correlations are available for IMs such as cumulative absolute velocity, CAV (EPRI, 1988) and arias intensity, IA (Arias, 1970), which are strongly influenced by cumulative ground motion features, and ...
Unlike the traditional smooth tests always based on parametric residuals, our method requires nonparametric estimation of the conditional cumulative distribution function (CDF). The proposed smooth test statistics are asymptotically chi-squar...