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Full-Text Articles in Physical Sciences and Mathematics
Estimation Of The Parameters In A Spatial Regressive-Autoregressive Model Using Ord's Eigenvalue Method, Sajib Mahmud Mahmud Tonmoy
Estimation Of The Parameters In A Spatial Regressive-Autoregressive Model Using Ord's Eigenvalue Method, Sajib Mahmud Mahmud Tonmoy
UNLV Theses, Dissertations, Professional Papers, and Capstones
In this thesis, we study one of Ord's (1975) global spatial regression models.
Ord considered spatial regressive-autoregressive models to describe the interaction
between location and a response variable in the presence of several covariates. He also
developed a practical estimation method for the parameters of this regression model
using the eigenvalues of a weight matrix that captures the contiguity of locations.
We review the theoretical aspects of his estimation method and implement it in the
statistical package R.
We also implement Ord's methods on the Columbus, Ohio, crime data set from the
year 1980, which involves the crime rate of …
The Doubly Adaptive Lasso Methods For Time Series Analysis, Zi Zhen Liu
The Doubly Adaptive Lasso Methods For Time Series Analysis, Zi Zhen Liu
Electronic Thesis and Dissertation Repository
In this thesis, we propose a systematic approach called the doubly adaptive LASSO tailored to time series analysis, which includes four specific methods for four time series models, respectively:
The PAC-weighted adaptive LASSO for univariate autoregressive (AR) models. Although the LASSO methodology has been applied to AR models, the existing methods in the literature ignore the temporal dependence information embedded in AR time series data. Consequently, the methods may not reflect the characteristics of underlying AR processes, especially, the lag order of AR models. The PAC-weighted adaptive LASSO incorporates the partial autocorrelation (PAC) into the adaptive LASSO weights. The PAC-weighted …
A Robust Estimate For The Bifurcating Autoregressive Model With Application To Cell Lineage Data, Tamer M. E. Elbayoumi
A Robust Estimate For The Bifurcating Autoregressive Model With Application To Cell Lineage Data, Tamer M. E. Elbayoumi
Dissertations
The bifurcating autoregressive model (BAR) is commonly used to model binary tree data. One application for this model relates to cell lineage data in biology. The purpose of studying the cell lineage process is to know whether the observed correlations between related cells are due to similarities in the environmental, inherited effects, or a combination of both of them. Because outliers in this kind of data are quite common, the need for a robust estimation procedure is necessary. A weighted L1 (WL1) estimate for estimating the parameters of the BAR model is considered. When the weights are constant, the estimate …