Critical gap estimation by numerical and statistical highest likelihood search

Many traffic situations require drivers to cross or merge into a stream having higher priority. Gap acceptance theory enables us to model such processes to analyse traffic operation. This discussion demonstrated that numerical search fine tuned by statistical analysis can be used to determine the most likely critical gap for a sample of drivers, based on their largest rejected gap and accepted gap. This method shares some common features with the Maximum Likelihood Estimation technique (Troutbeck 1992) but lends itself well to contemporary analysis tools such as spreadsheet and is particularly analytically transparent. This method is considered not to bias estimation of critical gap due to very small rejected gaps or very large rejected gaps. However, it requires a sufficiently large sample that there is reasonable representation of largest rejected gap/accepted gap pairs within a fairly narrow highest likelihood search band.

Political selection and the relative age effect

In this paper we present substantial evidence for the existence of a bias in the distribution of births of leading US politicians in favor of those that have been the oldest in their cohort at school. This “relative age effect” has been proven to influence performance at school and in sports,but evidence on its impact on people’s vocational success has been rare. We find a marked break in the density of birthdate of politicians using a maximum likelihood test and McCrary’s (2008) nonparametric test. We conjecture that being relatively old in a peer group may create long term advantages which can create a significant role in the ability to succeed in a highly competitive environment like the race for top political offices in the USA. The magnitude of the effect we estimate is larger than what most other studies on the relative age effect for a broader (adult) population find, but is in general in line with studies that look at populations in high-competition environments.

Econometric Modelling with Time Series : Specification, Estimation and Testing

This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

Parameter estimation of structural commodity price models

Commodity price modeling is normally approached in terms of structural time-series models, in which the different components (states) have a financial interpretation. The parameters of these models can be estimated using maximum likelihood. This approach results in a non-linear parameter estimation problem and thus a key issue is how to obtain reliable initial estimates. In this paper, we focus on the initial parameter estimation problem for the Schwartz-Smith two-factor model commonly used in asset valuation. We propose the use of a two-step method. The first step considers a univariate model based only on the spot price and uses a transfer function model to obtain initial estimates of the fundamental parameters. The second step uses the estimates obtained in the first step to initialize a re-parameterized state-space-innovations based estimator, which includes information related to future prices. The second step refines the estimates obtained in the first step and also gives estimates of the remaining parameters in the model. This paper is part tutorial in nature and gives an introduction to aspects of commodity price modeling and the associated parameter estimation problem.

Suggestive linkage of 2p22-25 and 11q12-13 with low bone mineral density at the lumbar spine in the Irish population

Osteoporosis is a disease characterized by low bone mineral density (BMD) and poor bone quality. Peak bone density is achieved by the third decade of life, after which bone is maintained by a balanced cycle of bone resorption and synthesis. Age-related bone loss occurs as the bone resorption phase outweighs the bone synthesis phase of bone metabolism. Heritability accounts for up to 90% of the variability in BMD. Chromosomal loci including 1p36, 2p22-25, 11q12-13, parathyroid hormone receptor type 1 (PTHR1), interleukin-6 (IL-6), interleukin 1 alpha (IL-1α) and type II collagen A1/vitamin D receptor (COL11A1/VDR) have been linked or shown suggestive linkage with BMD in other populations. To determine whether these loci predispose to low BMD in the Irish population, we investigated 24 microsatellite markers at 7 chromosomal loci by linkage studies in 175 Irish families of probands with primary low BMD (T-score ≤ -1.5). Nonparametric analysis was performed using the maximum likelihood variance estimation and traditional Haseman-Elston tests on the Mapmaker/Sibs program. Suggestive evidence of linkage was observed with lumbar spine BMD at 2p22-25 (maximum LOD score 2.76) and 11q12-13 (MLS 2.55). One region, 1p36, approached suggestive linkage with femoral neck BMD (MLS 2.17). In addition, seven markers achieved LOD scores > 1.0, D2S149, D11S1313, D11S987, D11S1314 including those encompassing the PTHR1 (D3S3559, D3S1289) for lumbar spine BMD and D2S149 for femoral neck BMD. Our data suggest that genes within a these chromosomal regions are contributing to a predisposition to low BMD in the Irish population.

Iterative estimating equations: Linear convergence and asymptotic properties

We propose an iterative estimating equations procedure for analysis of longitudinal data. We show that, under very mild conditions, the probability that the procedure converges at an exponential rate tends to one as the sample size increases to infinity. Furthermore, we show that the limiting estimator is consistent and asymptotically efficient, as expected. The method applies to semiparametric regression models with unspecified covariances among the observations. In the special case of linear models, the procedure reduces to iterative reweighted least squares. Finite sample performance of the procedure is studied by simulations, and compared with other methods. A numerical example from a medical study is considered to illustrate the application of the method.

Error, Bias, and Long-Branch Attraction in Data for Two Chloroplast Photosystem Genes in Seed Plants

Sequences of two chloroplast photosystem genes, psaA and psbB, together comprising about 3,500 bp, were obtained for all five major groups of extant seed plants and several outgroups among other vascular plants. Strongly supported, but significantly conflicting, phylogenetic signals were obtained in parsimony analyses from partitions of the data into first and second codon positions versus third positions. In the former, both genes agreed on a monophyletic gymnosperms, with Gnetales closely related to certain conifers. In the latter, Gnetales are inferred to be the sister group of all other seed plants, with gymnosperms paraphyletic. None of the data supported the modern ‘‘anthophyte hypothesis,’’ which places Gnetales as the sister group of flowering plants. A series of simulation studies were undertaken to examine the error rate for parsimony inference. Three kinds of errors were examined: random error, systematic bias (both properties of finite data sets), and statistical inconsistency owing to long-branch attraction (an asymptotic property). Parsimony reconstructions were extremely biased for third-position data for psbB. Regardless of the true underlying tree, a tree in which Gnetales are sister to all other seed plants was likely to be reconstructed for these data. None of the combinations of genes or partitions permits the anthophyte tree to be reconstructed with high probability. Simulations of progressively larger data sets indicate the existence of long-branch attraction (statistical inconsistency) for third-position psbB data if either the anthophyte tree or the gymnosperm tree is correct. This is also true for the anthophyte tree using either psaA third positions or psbB first and second positions. A factor contributing to bias and inconsistency is extremely short branches at the base of the seed plant radiation, coupled with extremely high rates in Gnetales and nonseed plant outgroups. M. J. Sanderson,* M. F. Wojciechowski,*† J.-M. Hu,* T. Sher Khan,* and S. G. Brady

Mutation frequency of non-ESBL phenotype SENTRY (Asia-Pacific) isolates of Klebsiella pneumoniae conversion to an ESBL positive phenotype

Extended spectrum β-lactamases or ESBLs, which are derived from non-ESBL precursors by point mutation of β-lactamase genes (bla), are spreading rapidly all over the world and have caused considerable problems in the treatment of infections caused by bacteria which harbour them. The mechanism of this resistance is not fully understood and a better understanding of these mechanisms might significantly impact on choosing proper diagnostic and treatment strategies. Previous work on SHV β-lactamase gene, blaSHV, has shown that only Klebsiella pneumoniae strains which contain plasmid-borne blaSHV are able to mutate to phenotypically ESBL-positive strains and there was also evidence of an increase in blaSHV copy number. Therefore, it was hypothesised that although specific point mutation is essential for acquisition of ESBL activity, it is not yet enough, and blaSHV copy number amplification is also essential for an ESBL-positive phenotype, with homologous recombination being the likely mechanism of blaSHV copy number expansion. In this study, we investigated the mutation rate of non-ESBL expressing K. pneumoniae isolates to an ESBL-positive status by using the MSS-maximum likelihood method. Our data showed that blaSHV mutation rate of a non-ESBL expressing isolate is lower than the mutation rate of the other single base changes on the chromosome, even with a plasmid-borne blaSHV gene. On the other hand, mutation rate from a low MIC ESBL-positive (≤ 8 µg/mL for cefotaxime) to high MIC ESBL-positive (≥16 µg/mL for cefotaxime) is very high. This is because only gene copy number increase is needed which is probably mediated by homologous recombination that typically takes place at a much higher frequencies than point mutations. Using a subinhibitory concentration of novobiocin, as a homologous recombination inhibitor, revealed that this is the case.

Measuring cognitive and dispositional characteristics of creativity in elementary students

This article describes the theoretical underpinning and development of a measurement instrument that provides teachers with a tool to observe the personal creativity characteristics of individual students. The instrument was developed by compiling a list of characteristics derived from the literature to be indicative of the personal characteristics of creative people. The list was then reduced by grouping like characteristics to 9 cognitive and dispositional traits that were considered appropriate for elementary students. The 9-item instrument was then administered in 24 classrooms to 520 Year 6 and Year 7 students. Factor analysis using maximum likelihood extraction with an oblimin rotation revealed a single factor with an eigenvalue greater than 1 and accounting for 63% of the variance. All 9 items on this factor loaded at .72 or greater. The results indicated that the Creativity Checklist has very high internal consistency and is a reliable measurement instrument (a = .93).

Multivariate methods to identify cancer-related symptom clusters

Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

Phylogenetic analysis of polyomaviruses based on their complete genomes

Perez-Losada et al. [1] analyzed 72 complete genomes corresponding to nine mammalian (67 strains) and 2 avian (5 strains) polyomavirus species using maximum likelihood and Bayesian methods of phylogenetic inference. Because some data of 2 genomes in their work are now not available in GenBank, in this work, we analyze the phylogenetic relationship of the remaining 70 complete genomes corresponding to nine mammalian (65 strains) and two avian (5 strains) polyomavirus species using a dynamical language model approach developed by our group (Yu et al., [26]). This distance method does not require sequence alignment for deriving species phylogeny based on overall similarities of the complete genomes. Our best tree separates the bird polyomaviruses (avian polyomaviruses and goose hemorrhagic polymaviruses) from the mammalian polyomaviruses, which supports the idea of splitting the genus into two subgenera. Such a split is consistent with the different viral life strategies of each group. In the mammalian polyomavirus subgenera, mouse polyomaviruses (MPV), simian viruses 40 (SV40), BK viruses (BKV) and JC viruses (JCV) are grouped as different branches as expected. The topology of our best tree is quite similar to that of the tree constructed by Perez-Losada et al.