Modified Fixed Effects Estimation of Technical Inefficiency

We consider method of moment fixed effects (FE) estimation of technical inefficiency. When N, the number of cross sectional observations, is large it ispossible to obtain consistent central moments of the population distribution of the inefficiencies. It is well-known that the traditional FE estimator may be seriously upward biased when N is large and T, the number of time observations, is small. Based on the second central moment and a single parameter distributional assumption on the inefficiencies, we obtain unbiased technical inefficiencies in large N settings. The proposed methodology bridges traditional FE and maximum likelihood estimation – bias is reduced without the random effects assumption.

Optimal IV estimation of systems with stochastic regressors and var disturbances with applications to dynamic systems

This paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FG LS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FG LS IV estimator to be asymptotic ally equivalent to an optimal G LS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and there by potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka [1976]. For the DG P used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well.

Refined Estimation of Earthquake Source Parameters: Methods, Applications and Scaling Relationships

The objective of this work of thesis is the refined estimations of source parameters. To such a purpose we used two different approaches, one in the frequency domain and the other in the time domain. In frequency domain, we analyzed the P- and S-wave displacement spectra to estimate spectral parameters, that is corner frequencies and low frequency spectral amplitudes. We used a parametric modeling approach which is combined with a multi-step, non-linear inversion strategy and includes the correction for attenuation and site effects. The iterative multi-step procedure was applied to about 700 microearthquakes in the moment range 1011-1014 N•m and recorded at the dense, wide-dynamic range, seismic networks operating in Southern Apennines (Italy). The analysis of the source parameters is often complicated when we are not able to model the propagation accurately. In this case the empirical Green function approach is a very useful tool to study the seismic source properties. In fact the Empirical Green Functions (EGFs) consent to represent the contribution of propagation and site effects to signal without using approximate velocity models. An EGF is a recorded three-component set of time-histories of a small earthquake whose source mechanism and propagation path are similar to those of the master event. Thus, in time domain, the deconvolution method of Vallée (2004) was applied to calculate the source time functions (RSTFs) and to accurately estimate source size and rupture velocity. This technique was applied to 1) large event, that is Mw=6.3 2009 L’Aquila mainshock (Central Italy), 2) moderate events, that is cluster of earthquakes of 2009 L’Aquila sequence with moment magnitude ranging between 3 and 5.6, 3) small event, i.e. Mw=2.9 Laviano mainshock (Southern Italy).

Kernel Estimation of Rate Function for Recurrent Event Data

Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users.

Consistent estimation of the fixed effects ordered logit model

The paper considers panel data methods for estimating ordered logit models with individual-specific correlated unobserved heterogeneity. We show that a popular approach is inconsistent, whereas some consistent and efficient estimators are available, including minimum distance and generalized method-of-moment estimators. A Monte Carlo study reveals the good properties of an alternative estimator that has not been considered in econometric applications before, is simple to implement and almost as efficient. An illustrative application based on data from the German Socio-Economic Panel confirms the large negative effect of unemployment on life satisfaction that has been found in the previous literature.

Portfolio efficiency tests with conditioning information using empirical likelihood estimation

We evaluate the use of Generalized Empirical Likelihood (GEL) estimators in portfolios efficiency tests for asset pricing models in the presence of conditional information. Estimators from GEL family presents some optimal statistical properties, such as robustness to misspecification and better properties in finite samples. Unlike GMM, the bias for GEL estimators do not increase as more moment conditions are included, which is expected in conditional efficiency analysis. We found some evidences that estimators from GEL class really performs differently in small samples, where efficiency tests using GEL generate lower estimates compared to tests using the standard approach with GMM. With Monte Carlo experiments we see that GEL has better performance when distortions are present in data, especially under heavy tails and Gaussian shocks.

The practicality of adaptive phase estimation

Adaptive phase estimation is the process of estimating the phase of an electromagnetic field via a continually changing measurement. The measurement is varied in an attempt to optimize it at each moment. In this paper, we show that adaptive phase estimation is more accurate than nonadaptive phase estimation for continuous beams of light even when small time delays in the feedback are present. (c) 2005 Pleiades Publishing Inc.

Using Inside-Outside Algorithm for Estimation of the Offspring Distribution in Multitype Branching Processes

Multitype branching processes (MTBP) model branching structures, where the nodes of the resulting tree are particles of different types. Usually such a process is not observable in the sense of the whole tree, but only as the “generation” at a given moment in time, which consists of the number of particles of every type. This requires an EM-type algorithm to obtain a maximum likelihood (ML) estimate of the parameters of the branching process. Using a version of the inside-outside algorithm for stochastic context-free grammars (SCFG), such an estimate could be obtained for the offspring distribution of the process.

Em Estimation of the Offspring Distribution in Mutitype Branching Processes - a Model in Cell Kinetics

2000 Mathematics Subject Classification: 60J80, 60J85, 62P10, 92D25.

Estimation of the Offspring and Immigration Mean Vectors for Bisexual Branching Processes with Immigration of Females and Males

2000 Mathematics Subject Classification: 60J80, 62M05.

A Note on Bayesian Estimation for the Negative-Binomial Model

2000 Mathematics Subject Classification: 62F15.

Scaphoid Fracture Nonunion: Correlation Of Radiographic Imaging, Proximal Fragment Histologic Viability Evaluation, And Estimation Of Viability At Surgery: Diagnosis Of Scaphoid Pseudarthrosis.

The purpose of this study was to correlate the pre-operative imaging, vascularity of the proximal pole, and histology of the proximal pole bone of established scaphoid fracture non-union. This was a prospective non-controlled experimental study. Patients were evaluated pre-operatively for necrosis of the proximal scaphoid fragment by radiography, computed tomography (CT) and magnetic resonance imaging (MRI). Vascular status of the proximal scaphoid was determined intra-operatively, demonstrating the presence or absence of puncate bone bleeding. Samples were harvested from the proximal scaphoid fragment and sent for pathological examination. We determined the association between the imaging and intra-operative examination and histological findings. We evaluated 19 male patients diagnosed with scaphoid nonunion. CT evaluation showed no correlation to scaphoid proximal fragment necrosis. MRI showed marked low signal intensity on T1-weighted images that confirmed the histological diagnosis of necrosis in the proximal scaphoid fragment in all patients. Intra-operative assessment showed that 90% of bones had absence of intra-operative puncate bone bleeding, which was confirmed necrosis by microscopic examination. In scaphoid nonunion MRI images with marked low signal intensity on T1-weighted images and the absence of intra-operative puncate bone bleeding are strong indicatives of osteonecrosis of the proximal fragment.

PENCALC: a program for penetrance estimation in autosomal dominant diseases

We present a computer program developed for estimating penetrance rates in autosomal dominant diseases by means of family kinship and phenotype information contained within the pedigrees. The program also determines the exact 95% credibility interval for the penetrance estimate. Both executable (PenCalc for Windows) and web versions (PenCalcWeb) of the software are available. The web version enables further calculations, such as heterozygosity probabilities and assessment of offspring risks for all individuals in the pedigrees. Both programs can be accessed and down-loaded freely at the home-page address http://www.ib.usp.br/~otto/software.htm.

Load Ratio Estimation Through Striation Height and Spacing Analysis of an Aerospace Al Alloy 7475-T7351

It is well known that striation spacing may be related to the crack growth rate, da/dN, through Paris equation, as well as the maximum and minimum loads under service loading conditions. These loads define the load ratio, R, and are considered impossible to be evaluated from the inter-spacing striations analysis. In this way, this study discusses the methodology proposed by Furukawa to evaluate the maximum and minimum loads based on the experimental fact that the relative height of a striation, H, and the striation spacing, s, are strongly influenced by the load ratio, R. Fatigue tests in C(T) specimens were conducted on SAE 7475-T7351 Al alloy plates at room temperature and the results showed a straightforward correlation between the parameters H, s, and R. Measurements of striation height, H, were performed using scanning electron microscopy and field emission gun (FEG) after sectioning the specimen at a large inclined angle to amplify the height of the striations. The results showed that for increasing R the values of H/s tend to increase. Striation height, striation spacing, and load ratio correlations were obtained, which allows one to estimate service loadings from fatigue fracture surface survey.

Estimation and prediction of parameters and breeding values in soybean using REML/BLUP and Least Squares

The aim of this study was to compare REML/BLUP and Least Square procedures in the prediction and estimation of genetic parameters and breeding values in soybean progenies. F(2:3) and F(4:5) progenies were evaluated in the 2005/06 growing season and the F(2:4) and F(4:6) generations derived thereof were evaluated in 2006/07. These progenies were originated from two semi-early, experimental lines that differ in grain yield. The experiments were conducted in a lattice design and plots consisted of a 2 m row, spaced 0.5 m apart. The trait grain yield per plot was evaluated. It was observed that early selection is more efficient for the discrimination of the best lines from the F(4) generation onwards. No practical differences were observed between the least square and REML/BLUP procedures in the case of the models and simplifications for REML/BLUP used here.