Structural equation model (SEM) is a general approach to analyze multivariate data. It is a relatively comprehensive model and combines useful characteristics from many statistical approaches, thus enjoys a variety of advantages when dealing complex relationships. This report gives a brief introduction to SEM, focusing especially the comparison of SEM and OLS regression. A simple tutorial of how to apply SEM is also included with the introduction and comparison. SEM can be roughly seen as OLS regression added with features such as simultaneous estimation, latent factors and autocorrelation. Therefore, SEM enjoys a variety of advantages over OLS regression. However, it is not always the case that SEM will be the optimal choice. The biggest concern is the complexity of SEM, for simpler model will be preferable for researchers when the fitness is similar. Two simulation cases, one requires special features of SEM and one satisfies assumptions of OLS regression, are applied to illustrate the choice between SEM and OLS regression. A study using data from US life insurers in the year 1994 serves as a further illustration. The conclusion is when special features of SEM is required, SEM fits better and will be the better choice, while when OLS regression assumptions are satisfied, SEM and OLS regression will fit equally well, considering the complexity of SEM, OLS regression will be the better choice. / text

published_or_final_version / abstract / toc / Physics / Master / Master of Philosophy

<p>ix, [1] s., s. 1-7: sammanfattning, s. 8-142: 6 uppsatser</p> / digitalisering@umu

Mud-pulse telemetry is a method used for measurement-while-drilling (MWD)in the oil industry. The telemetry signals are corrupted by spurious mud pump noise consisting of a large number of harmonically related sinusoids. In order to denoise the signal, the noise parameters have to be tracked accurately in real time. There are well established parametric estimation techniques for determining various parameters of independent sinusoids. The iterative methods based on the linear prediction properties of the sinusoids provide a computationally e±cient way of solving the non linear optimization problem presented by these methods. However, owing to the large number of these sinusoids, incorporating the harmonic relationship in the problem becomes important. This thesis is aimed at solving the problem of estimating parameters of harmonically related sinusoids. We examine the efficacy of IQML algorithm in estimating the parameters of the telemetry signal for varying SNRs and data lengths. The IQML algorithm proves quite robust and successfully tracks both stationary and slowly varying frequency signals. Later, we propose an algorithm for fundamental frequency estimation which relies on the initial harmonic frequency estimate. The results of tests performed on synthetic data that imitates real field data are presented. The analysis of the simulation results shows that the proposed method manages to remove noise causing sinusoids in the telemetry signal to a great extent. The low computational complexity of the algorithm also makes for an easy implementation on field where computational power is limited.

No description available.

No description available.

Human capital is increasingly believed to play an indispensable role in the growth process; however, adequately measuring its stock remains controversial. Because the estimated impact that human capital has on economic growth is sensitive to the measure of human capital, accurate and consistent measures are desirable. While many measures have been developed, most rely on some proxy of educational experience and are thus plagued with limitations. In this study, I adopt a lifetime earnings approach to estimate the monetary value of the human capital stock for New Zealand. I find that the country's working human capital increased by half between 1981 and 2001, mainly due to rising employment level. This stock was well over double that of physical capital. I also model human capital as a latent variable using a Partial Least Squares approach. Exploratory analyses on a number of countries show that age, gender and education combined can capture 65-97 percent of the explained variation in human capital. JEL Classifications: J24, O47.

This dissertation addresses the problem of scanning the geometry of real objects and building accurate computer models of those objects. We present a complete system which employs a structured light scanner to acquire 3D views of objects from multiple viewpoints. These multiple views, expressed in a sensor-oriented coordinate system, are then registered into a model-centred coordinate system, before being integrated into a single mesh describing the object's geometry. Line of sight constraints forbid any single view from capturing the entire surface of an object, so multiple scans must be performed. We have developed registration techniques which may register all of the views simultaneously, resulting in a globally optimal solution. Statistical error modeling of the sensor, and the use of these models in the registration process, forms a key part of the research. It is motiviated by the observation that all measurements are subject to some degree of random measurement error. The true values of these errors cannot be determined, however their statistical properties may be modeled. Our registration system utilises these error models to improve registration accuracy, and to allow the accuracy of the registration to be estimated. The resulting system is a flexible platform for 3D data capture and modeling. It may be used in conjunction with the structured light scanner, or 3D data acquired from any other source. We demonstrate this capability with models constructed from sources such as laser range finders and scanning touch probe systems. The contributions of this thesis are as follows: a novel stereo matching algorithm which permits the estimation of stereo disparity as well as the uncertainty in the disparity, development of a practical 3D vision sensor based on structured light techniques, two novel algorithms for performing simultaneous multiple view point set registration, while supporting individual point error models and estimating the uncertainty in the registration solution, a novel algorithm for efficiently solving the multiple view registration problem, and the implementation of a number of existing surface correspondence and reconstruction techniques, permitting the development of an integrated 3D vision system for capturing and modeling 3D objects.

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1994. / Vita. Abstract. Includes bibliographical references (leaves 156-160). Also available via the Internet.

Thesis (M.S.)--Ohio University, August, 1998. / Title from PDF t.p.