DSpace 集合:
http://hdl.handle.net/11455/18449
2021-04-12T02:47:48ZEstimation of abundance from presence–absence maps using cluster models
http://hdl.handle.net/11455/99156
標題: Estimation of abundance from presence–absence maps using cluster models
作者: Richard Huggins; Wen-Han Hwang; Jakub Stoklosa3; 黃文瀚
摘要: A presence–absence map consists of indicators of the occurrence or nonoccurrence of a given species in each cell over a grid, without counting the number of individuals in a cell once it is known it is occupied. They are commonly used to estimate the distribution of a species, but our interest is in using these data to estimate the abundance of the species. In practice, certain types of species (in particular flora types) may be spatially clustered. For example, some plant communities will naturally group together according to similar environmental characteristics within a given area. To estimate abundance, we develop an approach based on clustered negative binomial models with unknown cluster sizes. Our approach uses working clusters of cells to construct an estimator which we show is consistent. We also introduce a new concept called super-clustering used to estimate components of the standard errors and interval estimators. A simulation study is conducted to examine the performance of the estimators and they are applied to real data.Robust split-plot designs for model misspecification
http://hdl.handle.net/11455/99155
標題: Robust split-plot designs for model misspecification
作者: Chang-Yun Lin; 林長鋆
摘要: Many existing methods for constructing optimal split-plot designs, such as D-optimal or A-optimal designs, focus only on minimizing the variance of the parameter estimates for the fitted model. However, the true model is usually more complicated; hence, the fitted model is often misspecified. If significant effects not included in the model exist, then the estimates could be highly biased. Therefore a good split-plot design should be able to simultaneously control the variance and the bias of the estimates. In this article, I propose a new method for constructing optimal split-plot designs that are robust under model misspecification. Four examples are provided to demonstrate that my method can produce efficient split-plot designs with smaller overall aliasing. Simulation studies are performed to verify that the robust designs I construct have high power, low false discovery rate, and small mean squared error.Robust multistratum baseline designs
http://hdl.handle.net/11455/99154
標題: Robust multistratum baseline designs
作者: Chang-Yun Lin; Po Yang; 林長鋆
摘要: Baseline designs have received considerable attention recently. Most existing methods for finding best baseline designs were developed for completely randomized experiments. How to select baseline designs for experiments under multistratum structures has not been studied in the literature. The purpose of this paper is to fill this gap and extend the use of the baseline design for experiments with complex structures, such as split-plot experiments. A framework for baseline designs under multistratum structures is established and a generalized minimax -criterion for selecting multistratum baseline designs which are efficient and model robust is proposed. The coordinate-exchange algorithm is applied and robust baseline designs under split-plot, split-split-plot, and block-split-plot structures, which can be constructed via nesting operators repeatedly, are exemplified. A real case study for industrial experiments is provided to demonstrate the application and data analysis of multistratum baseline designs.Robust designs with high projection efficiency
http://hdl.handle.net/11455/99153
標題: Robust designs with high projection efficiency
作者: Chang‐Yun Lin; 林長鋆
摘要: Alphabetic optimality criteria, such as the D, A, and I criteria, require specifying a model to select optimal designs. They are not model‐free, and the designs obtained by them may not be robust. Recently, many extensions of the D and A criteria have been proposed for selecting robust designs with high estimation efficiency. However, approaches for finding robust designs with high prediction efficiency are rarely studied in the literature. In this paper, we propose a compound criterion and apply the coordinate‐exchange 2‐phase local search algorithm to generate robust designs with high estimation, high prediction, or balanced estimation and prediction efficiency for projective submodels. Examples demonstrate that the designs obtained by our method have better projection efficiency than many existing designs.