Testing the normality assumption in the sample selection model with an application to travel demand

In this paper we introduce a test for the normality assumption in the sample selection model.The test is based on a generalization of a semi-nonparametric maximum likelihood method.In this estimation method,the distribution of the error erms is approximated by a Hermite series,with normality as a special case.Because all parameters of the model are estimated both under normality and in the more general specification,we can est for normality using the likeli- hood ratio approach.This est has reasonable power as is shown by a simulation study.Finally,we apply the generalized semi-nonparametric maximum likeli- hood estimation method and the normality est o a model of car ownership and car use.The assumption of normal distributed error erms is rejected and we provide estimates of the sample selection model that are consisten .

Genotypic status of the TbAT1/P2 adenosine transporter of Trypanosoma brucei gambiense isolates from northwestern Uganda following melarsoprol withdrawal

Human African trypanosomiasis (HAT) manifests as a chronic infection caused by <i>Trypanosoma brucei gambiense</i>, or as a more acute form due to <i>T. b. rhodesiense</i>. Both manifestations occur in Uganda and melarsoprol use against the former was jeopardised in the 1990s as reports of reduced efficacy increased to the point where it was dismissed as first-line treatment at some treatment centers. Previous work to elucidate possible mechanisms leading to melarsoprol resistance pointed to a P2 type adenosine transporter known to mediate melarsoprol uptake and previously shown to be mutated in significant numbers of patients not responding to the drug. Our present findings indicate that there is a low prevalence of mutants in foci where melarsoprol relapses are infrequent. In addition we observe that at the Omugo focus where the drug was withdrawn as first line over 6 years ago, the mutant alleles have disappeared, suggesting that drug pressure is responsible for fuelling their spread. Thus constant monitoring for mutants could play a key role in cost-effective HAT management by identifying which foci can still use the less logistically demanding melarsoprol as opposed to the alternative drug eflornithine. What is required now is a simple method for identifying such mutants at the point of care, enabling practitioners to make informed prescriptions at first diagnosis

Stijging gehalte vrije vetzuren bij automatisch melken

Sinds de invoering van de melkrobot op bedrijven is te zien dat het gemiddelde gehalte aan vrije vetzuren omhoog gaat. Sommige bedrijven kampen zelfs met een korting voor vrije vetzuren

Testing the normality assumption in the sample selection model with an application to travel demand

In this paper we introduce a test for the normality assumption in the sample selection model.The test is based on a generalization of a semi-nonparametric maximum likelihood method.In this estimation method,the distribution of the error erms is approximated by a Hermite series,with normality as a special case.Because all parameters of the model are estimated both under normality and in the more general specification,we can est for normality using the likeli- hood ratio approach.This est has reasonable power as is shown by a simulation study.Finally,we apply the generalized semi-nonparametric maximum likeli- hood estimation method and the normality est o a model of car ownership and car use.The assumption of normal distributed error erms is rejected and we provide estimates of the sample selection model that are consisten

Testing the normality assumption in the sample selection model with an application to travel demand

this paper we introduce a test for the normality assumption in sample selection models. The test is based from a generalization of a semi-nonparametric maximum likelihood method. In this estimation method, the distribution of the error term is approximated by a Hermite series, with normality a special case. Because all parameters of the model are estimated in bith the simple and more general specification, we can test for normality using the likelihood ratio approach. This test has reasonable power as is shown by a a simulation study. Finally, we apply the generalized semi-nonparametric maximum likelihood estimation method and the normality test to a model of car ownership and car use. The assumption of normal distributed error terms is rejected and we provide estimates of the sample selection model that are consistent. Keywords: semi-nonparametric maximum likelihood, density estimation, Hermite series, sample selection

Discussion of the results of the boundary-layer tests of an airfoil fitted with a rotary cylinder

The results of the velocity measurements in the boundary layer described in NACA-TM 411 are here discussed in greater detail. The measurements made were of the velocity distribution in the vicinity of an airfoil model fitted with a rotary cylinder and were undertaken for the purpose of obtaining a closer insight into the phenomena observed in experimenting with this model