Comparison of the Short Term Interest Rate Models: Parametric Versus Non Parametric Approach

Parametric versus non-parametric simulation

Most of ex-ante impact assessment policy models have been based on a parametric approach. We develop a novel non-parametric approach, called Inverse DEA. We use non parametric efficiency analysis for determining the farm’s technology and behaviour. Then, we compare the parametric approach and the Inverse DEA models to a known data generating process. We use a bio-economic model as a data genera...

Reinsurance Rate-making with Parametric and Non-parametric Models

Parametric vs Non - Parametric Generative Models

The contrast is exemplified by the following classification task. Let’s assume that we are given data, X , i.e. the observed variable and we want to determine its class label, Y, the unobserved (target) variable. A generative classifier, such as Naive Bayes, makes use of the joint distribution of X and Y, i.e. P(X ,Y) to perform this inference. While a discriminative classifier, such as a Logis...

A Non-Parametric Approach

Since China joined the WTO in 2001, the pressure for bank reforms has mounted as China ought to fully open up its financial market to foreign competition by 2006. Efficiency is key for domestic banks to survive in a liberalised environment, but it appears that the last hope for raising bank efficiency is through ownership reform. Whether ownership reform and foreign competition can solve China’...

A Parametric Model Approach for Quantification of Short Term QT Variability Uncorrelated with Heart Rate Variability

In this work we propose to assess the relation between HRV and QTV measured by an automatic delineator. A low order linear autoregressive model on RR versus QT interactions was used to explore short term relations and quantify the fractions of QTV correlated and not correlated with HRV. Power spectral density measures were estimated from the total QTV and from the two separated fractions using ...