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Examining Multiple Imputation For Measurement Error Correction In Count Data With Excess Zeros, Shalima Zalsha
Examining Multiple Imputation For Measurement Error Correction In Count Data With Excess Zeros, Shalima Zalsha
Statistical Science Theses and Dissertations
Measurement error and missing data are two common problems in wildlife population surveys. These data are collected from the environment and may be missing or measured with error when the observer’s ability to see the animal is obscured. Methods such as video transects for estimating red snapper abundance and aerial surveys for estimating moose population sizes are highly affected by these problems since total abundance will be underestimated if missing/mismeasured counts are ignored. We shall refer to this problem as visibility bias; it occurs when the true counts are observed when visibility is high, partially observed when visibility is low …
A Study Of Cusum Statistics On Bitcoin Transactions, Ivan Perez
A Study Of Cusum Statistics On Bitcoin Transactions, Ivan Perez
Theses and Dissertations
In this thesis, our objective is to study the relationship between transaction price and volume in the BTC/USD Coinbase exchange. In the second chapter, we develop a consecutive CUSUM algorithm to detect instantaneous changes in the arrival rate of market orders. We begin by estimating a baseline rate using the assumption of a local time-homogeneous Poisson process. Our observations lead us to reject the plausibility of a time-homogeneous Poisson model on a more global scale by using a chi squared test. We thus proceed to use CUSUM-based alarms to detect consecutive upward and downward changes in the arrival rate of …
Statistical Models And Analysis Of Univariate And Multivariate Degradation Data, Lochana Palayangoda
Statistical Models And Analysis Of Univariate And Multivariate Degradation Data, Lochana Palayangoda
Statistical Science Theses and Dissertations
For degradation data in reliability analysis, estimation of the first-passage time (FPT) distribution to a threshold provides valuable information on reliability characteristics. Recently, Balakrishnan and Qin (2019; Applied Stochastic Models in Business and Industry, 35:571-590) studied a nonparametric method to approximate the FPT distribution of such degradation processes if the underlying process type is unknown. In this thesis, we propose improved techniques based on saddlepoint approximation, which enhance upon their suggested methods. Numerical examples and Monte Carlo simulation studies are used to illustrate the advantages of the proposed techniques. Limitations of the improved techniques are discussed and some possible solutions …