Recently, Starns et al. (2008) collected source judgments for old items, which participants had claimed to be new, and found residual source discriminability depending on the old-new response bias. The finding was interpreted as evidence in favor of the multivariate signal-detection model but against the high-threshold model of source memory. According to the latter, “new” responses only follow...

The present study intended to verify if the inclusion of intensities above lactate threshold (LT) in the VO2/running speed regression (RSR) affects the estimation error of accumulated oxygen deficit (AOD) during a treadmill running performed by endurance-trained subjects. Fourteen male endurance-trained runners performed a sub maximal treadmill running test followed by an exhaustive supra maxim...

This paper addresses a new method of detecting tile defects. The tile image is changed to binary image by using a float threshold. Using linear regression of binary data gives a measure for classifying the defective. In order to detect a defective tile the defined measure is compared against a threshold which is estimated adaptively through a learning scheme using 4-folded cross validation algo...

This article introduces a method to determine the threshold of unimodal image histograms in a robust manner. It is based on a piecewise linear regression that finds the two segments that fit the descending slope of the histogram. The algorithm gives a good estimation of the threshold, and is practically insensitive to the noise distribution, to the quantity of objects to segment, and to random ...

Operational risk has become increasingly important topics for Chinese Commercial Banks in recent years. Considering the huge operational losses, Extreme value theory (EVT) has been recognized as a useful tool in analyzing such data. In this paper, we presented an ERMPOT (Exponential Regression Model and the Peaks-Over-Threshold) method to measure the operational risk. The ERM-POT method can lea...

The threshold and non-threshold, the Benchmark dose, a probabilistic method and categorical regression are introduced as quantitative methods used for food and diet safety assessment (FDSA). Statistical challenges are identified and origins of uncertainties in FDSA are addressed such as the quality of data bases, the choice of the response variable, the doseresponse (DR) model and the role of m...

This paper studies the existence for a set of countries of an inflation threshold above which its effect on economic growth is negative, considering the speed of transition from one inflation regime to the other. Using a panel data set of above 120 countries for the period after the Second World War, we apply a panel smooth transition regression (PSTR) model with fixed effects. The estimated th...

There is interest in extending the boosting algorithm (Schapire, 1990) to fit a wide range of regression problems. The threshold-based boosting algorithm for regression used an analogy between classification errors and big errors in regression. We focus on the practical aspects of this algorithm and compare it to other attempts to extend boosting to regression. The practical capabilities of thi...

Regression discontinuity models, where the probability of treatment jumps discretely when a running variable crosses a threshold, are commonly used to nonparametrically identify and estimate a local average treatment effect. We show that the derivative of this treatment effect with respect to the running variable is nonparametrically identified and easily estimated. Then, given a local policy i...

Reported efficacies from vaccine trials may depend heavily on the clinical case definition used in the trial. The dependence may be particularly striking for diseases such as malaria, in which no single case definition is appropriate. We used logistic regression modeling of the relationship between parasitemia and fever in data sets from Ghanaian children to determine the fraction of fevers att...