44 research outputs found
Technical Efficiency of Growth and Income Fund in Malaysia: An Application of Stochastic Frontier Analysis (SFA)
No full textAbstract Unit trust or mutual fund industry is an intensive and very popular topic in research. A unit trust is an investment scheme that pools monies from individuals or institutions who share the same investment and financial objectives. However, investors often involve to problem when making the selection of funds to be invested. Therefore, the purpose of this current study is to measure and analyze the relative efficiency of unit trust industry in Malaysia by using Stochastic Frontier Analysis (SFA) method for the year 2007, 2008 and 2009 from prospectuses and statements of the Securities Commission of Malaysia, consist of 20 growth and 14 income funds. In this study, specification of Battese and Coelli (1992) is employed to measure an efficiency scores. All data were analyzed using 5780 Nor Azlida Aleng et al. Frontier software Version 4.1 to obtain the maximum likelihood method to estimate the parameters of stochastic production. The finding shows that the mean efficiency scores of growth fund was efficient. Meanwhile the income fund showed its average score technical efficiency is not efficient, but has increased in each year which indicates the funds have performed well gradually. Hopefully with categorizing ranks of each fund based on their efficinecy, manage to assist the investors in making a wise decision for a great return
Analisis kecekapan relatif bagi industri saham amanah menggunakan pendekatan ekonometrik
No full textMakalah ini bertujuan untuk mengukur kecekapan relatif industri saham amanah di Malaysia menggunakan kaedah Analisis Sempadan Stokastik (ASS) bagi tahun 2003 dan 2004 yang terdiri daripada 65 buah dana daripada 16 buah syarikat pengurusan dana saham amanah di Malaysia. Dana yang dikaji dibahagikan kepada tiga jenis, iaitu pertumbuhan, pendapatan dan Islam/Syariah menggunakan spesifi kasi Batt ese dan Coelli (1992). Analisis data dan keputusan kajian menggunakan program Frontier Versi 4.1 (Coelli, 1996). Kecekapan merupakan pengukuran penting yang boleh digunakan untuk menilai perkembangan dan pertumbuhan ekonomi sesebuah negara
Outlier detection based on robust parameter estimates
No full textOutliers can influence the analysis of data in various different
ways. The outliers can lead to model misspecification, incorrect
analysis results and can make all estimation procedures
meaningless. In regression analysis, ordinary least square
estimation is most frequently used for estimation of the
parameters in the model. Unfortunately, this estimator is
sensitive to outliers. Thus, in this paper we proposed some
statistics for detection of outliers based on robust estimation,
namely least trimmed squares (LTS). A simulation study was
performed to prove that the alternative approach gives a better
results than OLS estimation to identify outliers
Analisis kecekapan relatif bagi industri saham amanah menggunakan pendekatan ekonometrik
No full textPurpose – This paper measures the relative efficiency of unit trust in Malaysia for the year 2003 and 2004, consisting of 65 funds from 16 unit trust management
company which are categorised into three types; growth fund, income fund, and Islamic fund. The importance of this study can help the investor/trustee to choose the most efficient fund. Design/Methodology/Approach – The study employed the production model by Battese and Coelli (1992). Frontier software Version 4.1 was used to analyse
the efficiency score of unit trust funds and to estimate the parameters of stochastic production using maximum likelihood method.Findings – Score efficiency analysis is important to measure the level of technical efficiency in the unit trust industry and other industries. The growth fund showed increasing efficiency score when tested funds were categorised depending on the type or the investment objectives. The mean of efficiency score for the growth fund in 2003 is 95% and 99% in 2004. Entirely, the income fund in 2003 was more efficient than 2004 with 100% mean efficiency in 2003 and 93% in 2004. However, both funds were still considered as excellent and efficient.Meanwhile, the Islamic fund had low efficiency scores with 73% in 2003 and 84% in 2004. Originality/Value – The paper investigated extensively the relative efficiency and highlights these to investors, policy makers of unit trust, the unit trust industry and other industries
Multilayer feed-forward neural network approach to lymphoma cancer data
No full textLymphoma is a cancer in the lymphatic cells of the immune system, called lymphocytes. One of the most important organ systems of the human body is the lymphatic or lymphoid system, which is a network of node-like structures located throughout the body. This system helps filter out bacteria and plays an important role in fighting diseases. However, just like any other organ system in the body, it is also exposed to developing cancers. The objective of the current study is to study from the view of MLFF neural network model the most significant factor that influences Hodgkin’s lymphoma. The input variables of MLFF neural network model are selected based on the significant variables of logistic regression (LR) model. The view from (MLFF) neural network model showed that two variables which were diffuse large B-Cell lymphoma (DLBCL) and hypertension status (HPT) were most influence of Hodgkin’s lymphoma
Assessing the efficiency of multilayer feed-forward neural network model: application to body mass index data
No full textA variety of statistical approaches have been used to find the directed dependencies among a set of interest variables and to identify the associated important factors. Among the most popular methods are proportional hazard regression and logistic regression. The aim of the current study is to suggest another approach by using a multilayer feed-forward neural network model (MLFF). Using body mass index (BMI) as the dependent variable, we identify its related and appropriate independent variables. In this study we put forth two MLFF models. Model 1 is where all the independent variables as identified in the literature are included, while Model 2 is where only variables found significance as a result from a multiple linear regression (MLR) analysis are included in the model. Analyses were done by using SPSS and MATLAB packages. As a result of the study, we found that the best MLFF model was the model which considered the input variables based on selection criteria for regression
Analisis Kecekapan Relatif bagi Industri Saham Amanah Menggunakan Pendekatan Ekonometrik
No full textMakalah ini bertujuan untuk mengukur kecekapan relatif industri saham amanah di Malaysia menggunakan kaedah Analisis Sempadan Stokastik (ASS) bagi tahun 2003 dan 2004 yang terdiri daripada 65 buah dana daripada 16 buah syarikat pengurusan dana saham amanah di Malaysia. Dana yang dikaji dibahagikan kepada tiga jenis, iaitu pertumbuhan, pendapatan dan Islam/Syariah menggunakan spesifi kasi Batt ese dan Coelli (1992). Analisis data dan keputusan kajian menggunakan program Frontier Versi 4.1 (Coelli, 1996). Kecekapan merupakan pengukuran penting yang boleh digunakan untuk menilai perkembangan dan pertumbuhan ekonomi sesebuah negara.
 
Basic concepts in biostatistics with step by step in SPSS
No full textBasic concepts in biostatistics using SPSS emphasizes on an early exposure of basic biostatistics in developing the research skill among the early undergraduate undertaking research project. The special of this book is its integration with the SPSS software and friendly. This is to make sure that the readers can easily understand and design the research according to their research objectives. This book is designed with a very basic and intermediate useful technique which includes parametric and nonparametric test, categorical data analysis and regression techniques. This book also provide a clear step by step approach through screenshot in SPSS that are very important for ensuring the readers in gaining a better understanding for interpreting the results. Through this book, it is hoped that the readers could plan their research by choosing the right selections of the right statistical test. Happy reading
Statistical analysis using SPSS Version 24
No full textThis book provides the best solution for students and researchers in understanding the basic concept and the right procedure for the data analysis. The main objective of this book is to guide and help students or researchers who are using Statistical Package for the Social Sciences (SPSS) software in performing the statistical methods in their applied research. This book is very easy to follow for beginners in SPSS by following simple step-by-step instructions. It is arranged in a way that it is user friendly, and is written in a simple language that can easily be understood by the users. This book will give a straightforward solution to students and can also be used as a guideline in performing the statistical test using statistical analysis tools. Hopefully this book will help students in making good presentations and conclusions based on the results obtained and provides valuable information on statistical methods in applied research
Statistical modeling via bootstrapping and weighted techniques based on variances
No full textMultiple logistic regression is a methodology of handling dependent variables with a binary outcome. This
method is becoming increasingly widespread as a statistical technique that represents a discrete probability model. Many studies have focused on the application but less on the methodology building. This study aims to provide an applied method for multiple logistic regression which is called modified Bayesian logistic regression modeling as an alternative technique for logistic regression analysis that focuses on a combination of the bootstrap method using SAS macro and weighted techniques based on variances using SAS algorithm. Data on oral cancer were applied to illustrate a real scenario of oral health data. This data will be applied to the multiple logistic regression algorithm and modified Bayesian logistic regression. Results from both cases are strongly supported by clinical studies. Through the proposed algorithm, the researcher will have an option whether to analyze the data with the usual or an alternative method. Final results indicate that the modified procedure can provide more efficient results especially for the case which involves statistical inferences
