Linear vs. log-linear unit-root specification: an application of mis-specification encompassing

The objective of this paper is to apply the mis-specification (M-S) encompassing perspective to the problem of choosing between linear and log-linear unit-root models. A simple M-S encompassing test, based on an auxiliary regression stemming from the conditional second moment, is proposed and its empirical size and power are investigated using Monte Carlo simulations. It is shown that by focusing on the conditional process the sampling distributions of the relevant statistics are well behaved under both the null and alternative hypotheses. The proposed M-S encompassing test is illustrated using US total disposable income quarterly data.

Taxonomic free sorting: a successful method with older consumers and a novel approach to preference mapping

Taxonomic free sorting (TFS) is a fast, reliable and new technique in sensory science. The method extends the typical free sorting task where stimuli are grouped according to similarities, by asking respondents to combine their groups two at a time to produce a hierarchy. Previously, TFS has been used for the visual assessment of packaging whereas this study extends the range of potential uses of the technique to incorporate full sensory analysis by the target consumer, which, when combined with hedonic liking scores, was used to generate a novel preference map. Furthermore, to fully evaluate the efficacy of using the sorting method, the technique was evaluated with a healthy older adult consumer group. Participants sorted eight products into groups and described their reason at each stage as they combined those groups, producing a consumer-specific vocabulary. This vocabulary was combined with hedonic data from a separate group of older adults, to give the external preference map. Taxonomic sorting is a simple, fast and effective method for use with older adults, and its combination with liking data can yield a preference map constructed entirely from target consumer data.

Software-based study of a non-sorting method for median calculation on a set of integer numbers

This paper presents a software-based study of a hardware-based non-sorting median calculation method on a set of integer numbers. The method divides the binary representation of each integer element in the set into bit slices in order to find the element located in the middle position. The method exhibits a linear complexity order and our analysis shows that the best performance in execution time is obtained when slices of 4-bit in size are used for 8-bit and 16-bit integers, in mostly any data set size. Results suggest that software implementation of bit slice method for median calculation outperforms sorting-based methods with increasing improvement for larger data set size. For data set sizes of N > 5, our simulations show an improvement of at least 40%.

Label-free enrichment of avian Leucocytozoon using flow cytometric sorting

The group of haemosporidian parasites is of general interest to basic and applied science, since several species infect mammals, leading to malaria and associated disease symptoms. Although the great majority of haemosporidian parasites appear in bird hosts, as in the case of Leucocytozoon buteonis, there is little genomic information about genetic aspects of their co-evolution with hosts. Consequently, there is a high need for parasite-enrichment strategies enabling further analyses of the genomes, namely without exposure to DNA-intercalating dyes. Here, we used flow cytometry without an additional labelling step to enrich L. buteonis from infected buzzard blood. A specific, defined area of two-dimensional scattergramms was sorted and the fraction was further analysed. The successful enrichment of L. buteonis in the sorted fraction was demonstrated by Giemsa-staining and qPCR revealing a clear increase of parasite-specific genes, while host-specific genes were significantly decreased. This is the first report describing a labelling-free enrichment approach of L. buteonis from infected buzzard blood. The enrichment of parasites presented here is free of nucleic acid-intercalating dyes which may interfere with fluorescence-based methods or subsequent sequencing approaches.

Bit-index sort: a fast non-comparison integer sorting algorithm for permutations

This paper describes a fast integer sorting algorithm, herein referred as Bit-index sort, which is a non-comparison sorting algorithm for partial per-mutations, with linear complexity order in execution time. Bit-index sort uses a bit-array to classify input sequences of distinct integers, and exploits built-in bit functions in C compilers supported by machine hardware to retrieve the ordered output sequence. Results show that Bit-index sort outperforms in execution time to quicksort and counting sort algorithms. A parallel approach for Bit-index sort using two simultaneous threads is included, which obtains speedups up to 1.6.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

The log-exponentiated Weibull regression model for interval-censored data

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

Generalized log-gamma regression models with cure fraction

In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.

Log-Burr XII regression models with censored data

In survival analysis applications, the failure rate function may frequently present a unimodal shape. In such case, the log-normal or log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the Burr XII distribution is proposed for modeling data with a unimodal failure rate function as an alternative to the log-logistic regression model. Assuming censored data, we consider a classic analysis, a Bayesian analysis and a jackknife estimator for the parameters of the proposed model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the log-logistic and log-Burr XII regression models. Besides, we use sensitivity analysis to detect influential or outlying observations, and residual analysis is used to check the assumptions in the model. Finally, we analyze a real data set under log-Buff XII regression models. (C) 2008 Published by Elsevier B.V.

Deviance residuals in generalised log-gamma regression models with censored observations

In this article, we compare three residuals based on the deviance component in generalised log-gamma regression models with censored observations. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. For all cases studied, the empirical distributions of the proposed residuals are in general symmetric around zero, but only a martingale-type residual presented negligible kurtosis for the majority of the cases studied. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for the martingale-type residual in generalised log-gamma regression models with censored data. A lifetime data set is analysed under log-gamma regression models and a model checking based on the martingale-type residual is performed.

The log-bimodal-skew-normal model. A geochemical application

The main objective of this paper is to study a logarithm extension of the bimodal skew normal model introduced by Elal-Olivero et al. [1]. The model can then be seen as an alternative to the log-normal model typically used for fitting positive data. We study some basic properties such as the distribution function and moments, and discuss maximum likelihood for parameter estimation. We report results of an application to a real data set related to nickel concentration in soil samples. Model fitting comparison with several alternative models indicates that the model proposed presents the best fit and so it can be quite useful in real applications for chemical data on substance concentration. Copyright (C) 2011 John Wiley & Sons, Ltd.

Simulation of Sawmill Yard Operations Using Software Agents

Bergkvist insjön AB is a sawmill yard which is capable of producing 350,000 cubic meter of timber every year this requires lot of internal resources. Sawmill operations can be classified as unloading, sorting, storage and production of timber. In the company we have trucks arriving at random they have to be unloaded and sent back at the earliest to avoid queuing up of trucks creating a problem for truck owners. The sawmill yard has to operate with two log stackers that does several tasks including transporting the logs from trucks to measurement station where the logs will be sorted into classes and dropped into pockets from pockets to the sorted timber yard where they are stored and finally from there to sawmill for final processing. The main issue that needs to be answered here is the lining up trucks that are waiting to be unload, creating a problem for both sawmill as well as the truck owners and given huge production volume, it is certain that handling of resources is top priority. A key challenge in handling of resources would be unloading of trucks and finding a way to optimize internal resources.To address this problem i have experimented on different ways of using internal resources, i have designed different cases, in case 1 we have both the log stackers working on sawmill and measurement station. The main objective of having this case is to make sawmill and measurement station to work all the time. Then in case 2, i have divided the work between both the log stackers, one log stacker will be working on sawmill and pocket_control and second log stacker will be working on measurement station and truck. Then in case 3 we have only one log stacker working on all the agents, this case was designed to reduce cost of production, as the experiment cannot be done in real-time due to operational cost, for this purpose simulation is used, preliminary investigation into simulation results suggested that case 2 is the best option has it reduced waiting time of trucks considerably when compared with other cases and it showed 50% increase in optimizing internal resources.

The attractiveness of the work is affected when production of handcrafted log houses moves indoors

Viewed from a historical perspective, a shift has occurred within the forestry and wood sector towards indoor work. In Sweden, the production of handcrafted log houses has now also begun to move indoors. With a point of departure in development processes within the log house sector involving working indoors, education, work attractiveness, between 2001-2005, the aim of this study was to compare indoor work with outdoor work, based on log house builders' experience of working on handcrafted log houses. Methods used in the interactive development project involving apprentices, experienced log house builders and researchers, were participation with continuous documentation of experiences and opinions; questions; interviews; and measurement of the work environment. The Attractive Work Model has been used in order to analyse perceptions and values. The changes, 15 out of 22 areas, were perceived both negatively and positively. Therefore, it can not be said that working on traditional, handcrafted log houses becomes more attractive if it is moved indoors. The majority wanted to work both outdoors and indoors, while most of the others only wanted to work outdoors. The results indicate that there is scope for developing more attractive work indoors by utilising experiences from log house builders and closely related activities such as the forestry and wood sector. Changes made within one area of work attractiveness affect other areas. Further research is needed both with regard to comparisons between indoor and outdoor work and regarding the interaction between the areas that are identified in the Attractive Work Model.