In optical coherence tomography (OCT), unbiased and low variance Doppler frequency estimators are desirable for blood velocity estimation. Hardware improvements in OCT mean that ever higher acquisition rates are possible. However, it is known that the Kasai autocorrelation estimator, unexpectedly, performs worse as acquisition rates increase. Here we suggest that maximum likelihood estimators (...

Many types of genetic analyses depend on estimates of allele frequencies. We consider the problem of allele-frequency estimation based on data from related individuals. The motivation for this work is data collected on the Hutterites, an isolated founder population, so we focus particularly on the case in which the relationships among the sampled individuals are specified by a large, complex pe...

3.1 Maximum likelihood estimates — in exponential families. Let (X, B) be a measurable space and {P θ , θ ∈ Θ} a measurable family of laws on (X, B), dominated by a σ-finite measure v. Let f (θ, x) be a jointly measurable version of the density (dP θ /dv)(x) by Theorem 1.3.3. For each x ∈ X, a maximum likelihood estimate (MLE) of θ is any θ ˆ = θ ˆ (x) such that f (ˆ θ, x) = sup{f (φ, x) : φ ∈ ...

In this thesis we study issues related to estimators behavior. We examine the general scalar measurement equation yn = h(θ) + vn, from which we wish to estimate the parameter θ. Specifically, we concentrate on problems where θ is a continuous parameter and the Fisher Information Measure (FIM) equal zero at isolated points θi. The well-known Cramér-Rao Lower Bound (CRLB) on the variance of any u...

This paper proposes and implements a tractable approach to detect group structure in panel data. The mechanism works by means of a panel structure model, which assumes that individuals form a number of homogeneous groups in a heterogeneous population. Within each group, the (linear) regression coefficients are the same, while they may be different across different groups. The econometrician is ...

We suggest an iterative approach to computing K-step maximum likelihood estimates (MLE) of the parametric components in semiparametric models based on their profile likelihoods. The higher order convergence rate of K-step MLE mainly depends on the precision of its initial estimate and the convergence rate of the nuisance functional parameter in the semiparametric model. Moreover, we can show th...

The blood flow in the human cardiovascular system obeys the laws of fluid mechanics. Investigation of the flow properties reveals that a correlation exists between the velocity in time and space. The possible changes in velocity are limited, since the blood velocity has a continuous profile in time and space. This paper presents a new estimator (STC-MLE), which incorporates the correlation prop...

Counts of a specific characteristic were obtained within regions defined on an object that was manufactured in proprietary setting. The count altered during production and resulted misaligned or overlapping data. A closed-formula maximum likelihood estimator (MLE) the new region means is derived using all available data independent Poisson model. MLE shown to be preferable estimators constructe...

♦ parameter space-Ω = {all θ} ♦ estimator-a random variable (or vector) ♦ estimate-a value (vector) derived from a realization ♦ (log)-likelihood function-n i=1 f (x i ; θ). ♦ maximum likelihood estimator (estimate)[mle]) is called an unbiased estimator of θ. Otherwise, it is said to be biased. ♦ parameter estimation by method of moments. Example 1: mle for the mean and variance of a random sam...