We propose one parametric and one non-parametric method for detection of monotone trends in nutrient concentrations in brackish waters. Both methods take into account that temporal variation in the quality of such waters can be strongly influenced by mixing of salt and fresh water, thus salinity is used as a classification variable in the trend analysis. With the non-parametric approach, Mann-K...

k-fold cross validation is a popular practical method to get a good estimate of the error rate of a learning algorithm. Here, the set of examples is first partitioned into k equal-sized folds. Each fold acts as a test set for evaluating the hypothesis learned on the other k − 1 folds. The average error across the k hypotheses is used as an estimate of the error rate. Although widely used, espec...

Importance sampling is a widely used variance reduction technique to compute sample quantiles such as value at risk. The variance of the weighted sample quantile estimator is usually a difficult quantity to compute. In this paper we present the exact convergence rate and asymptotic distributions of the bootstrap variance estimators for quantiles ofweighted empirical distributions. Under regular...

A study to compare different methods of estimation was conducted. The goal was to provide an estimate for the number of petal colors existing in the field by using a random sample of Lycoris longituba flowers taken from the field. Three methods of estimation were used to estimate the actual number of the colors in the field. Using the variance analysis, the maximum number of colors was obtained...

This article proposes an estimate of the odds ratio in a (2 £ 2) table obtained from studies in which the row totals are Ž xed by design, such as a phase II clinical trial. Our estimate,basedon themedianunbiasedestimateof the probabilitiesof success in the (2£2) table, will always be in the interval (0;1): Another estimate of the odds ratio which has such properties is obtained when adding .5 t...

The bias-variance decomposition of error provides useful insights into the error performance of a classifier as it is applied to different types of learning task. Most notably, it has been used to explain the extraordinary effectiveness of ensemble learning techniques. It is important that the research community have effective tools for assessing such explanations. To this end, techniques have ...

We propose robust tests as alternatives to the classical Wilks’ Lambda test in one-way MANOVA. The robust tests use highly robust and efficient multi-sample multivariate Sor MM-estimators instead of the empirical covariances. The properties of several robust test statistics are compared. Under the null hypothesis, the distribution of the test statistics is proportional to a chi-square distribut...

A joint fractionally integrated, error-correction andmultivariateGARCH (FIEC-BEKK) approach is applied to investigate hedging effectiveness using daily data 1995–2005. The findings reveal the proxied error-correction term has a long memory component that theoretically should affect hedging effectiveness.When the FIECmodel empirical conditions are satisfied, the FIEC-BEKK hedging strategy outper...

This paper describes an efficient randomised sphere cover classifier (αRSC), that reduces the training dataset size without loss of accuracy when compared to nearest neighbour classifiers. The motivation for developing this algorithm is the desire to have a non-deterministic, fast, instance-based classifier that performs well in isolation but is also ideal for use with ensembles. Essentially we...