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Articles 1 - 4 of 4
Full-Text Articles in Statistics and Probability
Fundamental Tradeoffs In Estimation Of Finite-State Hidden Markov Models, Justin Le
Fundamental Tradeoffs In Estimation Of Finite-State Hidden Markov Models, Justin Le
UNLV Theses, Dissertations, Professional Papers, and Capstones
Hidden Markov models (HMMs) constitute a broad and flexible class of statistical models that are widely used in studying processes that evolve over time and are only observable through the collection of noisy data. Two problems are essential to the use of HMMs: state estimation and parameter estimation. In state estimation, an algorithm estimates the sequence of states of the process that most likely generated a certain sequence of observations in the data. In parameter estimation, an algorithm computes the probability distributions that govern the time-evolution of states and the sampling of data. Although algorithms for the two problems are …
Bi-Directional Testing For Change Point Detection In Poisson Processes, Moinak Bhaduri
Bi-Directional Testing For Change Point Detection In Poisson Processes, Moinak Bhaduri
UNLV Theses, Dissertations, Professional Papers, and Capstones
Point processes often serve as a natural language to chronicle an event's temporal evolution, and significant changes in the flow, synonymous with non-stationarity, are usually triggered by assignable and frequently preventable causes, often heralding devastating ramifications. Examples include amplified restlessness of a volcano, increased frequencies of airplane crashes, hurricanes, mining mishaps, among others. Guessing these time points of changes, therefore, merits utmost care. Switching the way time traditionally propagates, we posit a new genre of bidirectional tests which, despite a frugal construct, prove to be exceedingly efficient in culling out non-stationarity under a wide spectrum of environments. A journey surveying …
Generalized Clusterwise Regression For Simultaneous Estimation Of Optimal Pavement Clusters And Performance Models, Mukesh Khadka
Generalized Clusterwise Regression For Simultaneous Estimation Of Optimal Pavement Clusters And Performance Models, Mukesh Khadka
UNLV Theses, Dissertations, Professional Papers, and Capstones
The existing state-of-the-art approach of Clusterwise Regression (CR) to estimate pavement performance models (PPMs) pre-specifies explanatory variables without testing their significance; as an input, this approach requires the number of clusters for a given data set. Time-consuming ‘trial and error’ methods are required to determine the optimal number of clusters. A common objective function is the minimization of the total sum of squared errors (SSE). Given that SSE decreases monotonically as a function of the number of clusters, the optimal number of clusters with minimum SSE always is the total number of data points. Hence, the minimization of SSE is …
Effects Of Inlet Conditions On Diffuser Outlet Performance, Zaccary A. Poots
Effects Of Inlet Conditions On Diffuser Outlet Performance, Zaccary A. Poots
UNLV Theses, Dissertations, Professional Papers, and Capstones
Building air distribution terminal system designers and system installers require accurate quantitative information on the performance of the installed system to achieve optimum efficiency and levels of human comfort. This requires field installation adjustment values from published ideal pressure loss, air distribution and sound generation installation performance. This study documents the air output performance of different installation configurations of six types of ceiling diffusers and compares the results to performance when installed according to ANSI/ASHRAE Standard 70-2006. A diffuser inlet supply plenum was designed for optimum flow and used to acquire a baseline set of data covering the six types …