We present a general methodology to incorporate fundamental economic factors to our previous theory of herding to describe bubbles and antibubbles. We start from the strong form of Rational Expectation and derive the general method to incorporate factors in addition to the log-periodic power law (LPPL) signature of herding developed in ours and others’ works. These factors include interest rate...

We first present an improvement of Kanatani’s subspace separation [8] for motion segmentation by newly introducing the affine space constraint . We point out that this improvement does not always fare well due to the effective noise it introduces. In order to judge which solution to adopt if different segmentations are obtained, we present two criteria: one is the standard F test; the other is ...

This report reviews and straightens methodologies to explore functional forms of man-landcover interrelations**. Tanaka and Nishii[7, 8, 9, 10, 12, 13], Nishii and Tanaka[4, 6], Nishii, Miyata, and Tanaka[5] have engaged in the analysis of deforestation by human population interactions. The basic strategy has been to use landcover data mashed up with cell-formed population density data. Two fac...

Akaike's criterion is used to test composite hypotheses ; for example to determine the order of AR models. A modiication is presented to test composite hypotheses given an upper-bound on the error of the rst kind (Neyman-Pearson). The presented theory is applied to AR order estimation and veriied by simulations. The experimental results are so good that we consider the AR order estimation probl...

To address order selection for an autoregressive model fitted to time series data, we propose a new information criterion. It has the benefits of the two wellknown model selection techniques, the Akaike information criterion and the Bayesian information criterion. When the data is generated from a finite order autoregression, the Bayesian information criterion is known to be consistent, and so ...

Order-selection criteria for vector autoregressive (AR) modeling are discussed. The performance of an order-selection criterion is optimal if the model of the selected order is the most accurate model in the considered set of estimated models: here vector AR models. Suboptimal performance can be a result of underfit or overfit. The Akaike information criterion (AIC) is an asymptotically unbiase...

BACKGROUND The Cox Proportional Hazard model is the most popular technique to analysis the effects of covariates on survival time but under certain circumstances parametric models may offer advantages over Cox's model. In this study we use Cox regression and alternative parametric models such as: Weibull, Exponential and Lognormal models to evaluate prognostic factors affecting survival of pati...

The relational approach to dependence estimation inevitably entails the necessity of choosing, at least, a sufficiently small relevance subset of training-set objects with which any newly occurring object will have to be compared for estimating its hidden target characteristic. If several comparison modalities are tentatively supposed by the observer, a relevance subset of them is to be additio...

The statistical information processing can be characterized by the likelihood function de ned by giving an explicit form for an approximation to the true distribution. This mathematical representation, which is usually called a model, is built based on not only the current data but also prior knowledge on the object and the objective of the analysis. Akaike 3) showed that the log-likelihood can...

Statistical model specification and validation raise crucial foundational problems whose pertinent resolution holds the key to learning from data by securing the reliability of frequentist inference. The paper questions the judiciousness of several current practices, including the theory-driven approach, and the Akaike-type model selection procedures, arguing that they often lead to unreliable ...