The Experts below are selected from a list of 28248 Experts worldwide ranked by ideXlab platform
Hilmi F. Kittani - One of the best experts on this subject based on the ideXlab platform.
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The Estimation of Logistic Probability Model of Binomial Data: Simulation Comparison
Journal of Mathematics and Statistics, 2008Co-Authors: Zaki. J. Al Sarraf, Faris M. Al Athari, Hilmi F. KittaniAbstract:Properties of various types of estimators of the regression coefficients in linear Logistic regression Models were considered. The estimators include those based on maximum likelihood, minimum chi-square and weighted least squares. The results of a large scale simulation investigation evaluating the moment properties of the estimators are presented for the case of Logistic Model with a single explanatory variable.
Zaki. J. Al Sarraf - One of the best experts on this subject based on the ideXlab platform.
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The Estimation of Logistic Probability Model of Binomial Data: Simulation Comparison
Journal of Mathematics and Statistics, 2008Co-Authors: Zaki. J. Al Sarraf, Faris M. Al Athari, Hilmi F. KittaniAbstract:Properties of various types of estimators of the regression coefficients in linear Logistic regression Models were considered. The estimators include those based on maximum likelihood, minimum chi-square and weighted least squares. The results of a large scale simulation investigation evaluating the moment properties of the estimators are presented for the case of Logistic Model with a single explanatory variable.
Pantelis Marinakis - One of the best experts on this subject based on the ideXlab platform.
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An investigation of earnings management and earnings manipulation in the UK
2011Co-Authors: Pantelis MarinakisAbstract:What causes managers to manipulate their financial statements? How best can shareholders or prospective investors, auditors, financial analysts and regulators detect earnings manipulations? Addressing these questions is of critical importance to the efficient functioning of capital markets. For an investor it can result to improved returns, for an auditor it can mean avoiding costly litigation, for an analyst it can mean avoiding a damaged reputation, and for a regulator it can lead to enhanced investor protection and fewer investment disasters. The objective of this thesis is two-fold. The first objective is to investigate the frequency and the magnitude of earnings management. Second, is to provide an analysis of the characteristics of companies discovered to manipulate earnings and the determinants of these manipulations. Exploratory interviews with the Financial Reporting Review Panel suggest that earnings manipulation usually results from escalating earnings management that after a certain stage violates accounting principles. This is analysed in a review of a series of companies publicly criticised for applying aggressive accounting practises. It is suggested that these cases involve specific accounting standards that require increased judgement from management. In order to gain a broader view of the extent that companies manage earnings, this thesis examines the distribution of earnings among thresholds such as zero earnings and earnings decreases. This thesis documents evidence of unusually low frequencies of small decreases in earnings and small losses and unusually high frequencies of small increases in earnings and small positive earnings. Additional evidence suggests that three components of earnings, cash flow from operations, changes in working capital and discretionary accruals, are used to achieve increases in earnings. Finally, this thesis presents evidence of the characteristics of firms that manipulate earnings and proposes a Model for detecting earnings manipulation. Companies found to manipulate earnings appear to have lower accrual quality, declining performance, weaker corporate governance structure, weaker balance sheet and increased leverage. The output of this investigation is a scaled Logistic Probability Model for discriminating accounting manipulations, where higher values suggest a greater Probability of manipulation.
Faris M. Al Athari - One of the best experts on this subject based on the ideXlab platform.
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The Estimation of Logistic Probability Model of Binomial Data: Simulation Comparison
Journal of Mathematics and Statistics, 2008Co-Authors: Zaki. J. Al Sarraf, Faris M. Al Athari, Hilmi F. KittaniAbstract:Properties of various types of estimators of the regression coefficients in linear Logistic regression Models were considered. The estimators include those based on maximum likelihood, minimum chi-square and weighted least squares. The results of a large scale simulation investigation evaluating the moment properties of the estimators are presented for the case of Logistic Model with a single explanatory variable.
Di Ekine - One of the best experts on this subject based on the ideXlab platform.
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Determinants of choice of crop grown in the floodplain among farmers in Rivers State, Nigeria
Journal of Agriculture Forestry and the Social Sciences, 2016Co-Authors: Me Ndubueze-ogaraku, Di EkineAbstract:This study examined the determinants of choice of crop grown in the floodplain among the farmers in Rivers State Nigeria. A simple random sampling technique was adopted to select 340 respondents. Descriptive statistics and Logistic Probability Model were the analytical technique used. The result shows that about 34.7 % of respondents were in the age group of 31- 40 years; womenfolk dominated the farming population with 63.5%. The Logistic regression results showed that farmers’ age and years of formal education were significant determinants of choice of crop grown in study area. The Wald statistics showed a statistical significant result which concludes that the choice of either growing cassava or fluted pumpkin in the study area was influenced by socio-economic characteristics of the farmers. It is recommended that farmers are advised to improve their level of education to enhance decision making ability on types of crops to grow in the floodplain farms. Keywords: Determinants, Farmers’ Choice, Crop, Floodplain, Rivers State
