A random sample of curves can be usually thought of as noisy realisations of a compound stochastic process X(t) = Z{W(t)}, where Z(t) produces random amplitude variation and W(t) produces random ...
Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...
This is a preview. Log in through your library . Abstract In this paper we investigate a broader semiparametric two-sample density ratio model based on two groups of right-censored data. A ...
The challenge of using small sample sizes for operational risk capital models fitted via maximum likelihood estimation is well recognized, yet the literature generally provides warning examples rather ...
In the process of loan pricing, stress testing, capital allocation, modeling of probability of default (PD) term structure and International Financial Reporting Standard 9 expected credit loss ...
The following data are taken from Lawless (1982, p.193) and represent the number of days it took rats painted with a carcinogen to develop carcinoma. The last 2 observations are censored data from a ...
The model stored in Example 14.3 is read in using the MODEL= option and the moving average terms are added using the %MA macro. The MA(1) model using maximum ...
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