-
On the Zero-One Inflated Poisson Distribution
Rafid Saeed Abdulrazak Alshkaki
Issue:
Volume 2, Issue 4, December 2016
Pages:
42-48
Received:
18 August 2016
Accepted:
10 September 2016
Published:
10 December 2016
DOI:
10.11648/j.ijsd.20160204.11
Downloads:
Views:
Abstract: In many sampling involving non negative integer data, the zeros are observed to be significantly higher than the expected assumed model. Such models are called zero-one inflated models. The zero inflated Poisson distribution was recently considered and studied due to its empirical needs and application. In this paper, an extension to the case of zero inflated case is considered, namely, the zero and one inflated Poisson distribution, along with some of its structural properties, and estimation of its parameters using the methods of moments and maximum likelihood estimators were obtained with three empirical examples as well.
Abstract: In many sampling involving non negative integer data, the zeros are observed to be significantly higher than the expected assumed model. Such models are called zero-one inflated models. The zero inflated Poisson distribution was recently considered and studied due to its empirical needs and application. In this paper, an extension to the case of ze...
Show More
-
Some Random Coefficient Models with Laplace Marginals
Bindu Krishnan,
Dais George
Issue:
Volume 2, Issue 4, December 2016
Pages:
49-53
Received:
30 October 2016
Accepted:
17 November 2016
Published:
17 December 2016
DOI:
10.11648/j.ijsd.20160204.12
Downloads:
Views:
Abstract: In this paper, we study a first order random coefficient autoregressive model with Laplace distribution as marginal. A random coefficient moving average model of order one with Laplace as marginal distribution is introduced and its properties are studied. By combining the two models, we develop a first order random coefficient autoregressive moving average model with Laplace marginal and discuss its properties. A first order random coefficient moving average process with generalized Laplace innovations is also obtained.
Abstract: In this paper, we study a first order random coefficient autoregressive model with Laplace distribution as marginal. A random coefficient moving average model of order one with Laplace as marginal distribution is introduced and its properties are studied. By combining the two models, we develop a first order random coefficient autoregressive moving...
Show More
-
The Optimal Investment Strategy Based on the Large-Scale Non-linear Constraint Optimization Methods
Li Yizhang,
Zhao Xinyu,
Chen Meng
Issue:
Volume 2, Issue 4, December 2016
Pages:
54-66
Received:
15 July 2016
Accepted:
17 November 2016
Published:
29 December 2016
DOI:
10.11648/j.ijsd.20160204.13
Downloads:
Views:
Abstract: We develop a model to determine an optimal investment strategy to improve the performance of undergraduate students in the US. Our model has three parts: In the first part, we collect data about the focus of other foundations’ investment by subjects and locations. We consider the charitable identity of the Goodgrant as well. Then we set out to decide our focus, which is to invest more on those schools with more minority races, lower educational performance, higher debt ratio and so on. In this part, we also classify the data into two groups, one for school selecting, and another for ROI determining. In the second part, as a data extraction, we build an efficient and intuitive model to rank the candidate schools in accordance with the correlation of our focus, using the PCA method. After that, the top 50 schools are selected as our target schools. In the third part, we make a key assumption that the social utility of a school has logarithmic relationship with the earnings of graduated students and the graduation rate. More over, we create a parameter k to denote the marginal rate of substitution (MRS) between the two factors above. After that, we come to define the ROI function of each target school as the incremental utility. We further discuss how to devise the best strategy with several methods. At last, we choose the improved PSO algorithm based on augmented Lagrange function. This algorithm is a typical method to solve the multivariable optimization problem with constraint conditions. Then we offer a recommending list by the cumulative ROI in five years. What’s more, our model is broad enough to accommodate any non-linear constraint optimization problem. Finally, we change the numerical value of parameter k to examine the sensitivity of our investment strategy. The result shows that our model is robust.
Abstract: We develop a model to determine an optimal investment strategy to improve the performance of undergraduate students in the US. Our model has three parts: In the first part, we collect data about the focus of other foundations’ investment by subjects and locations. We consider the charitable identity of the Goodgrant as well. Then we set out to deci...
Show More
-
On the Distribution of Risk of Migration and Its Estimation
Brijesh P. Singh,
Niraj K. Singh
Issue:
Volume 2, Issue 4, December 2016
Pages:
67-71
Received:
14 September 2016
Accepted:
21 November 2016
Published:
30 December 2016
DOI:
10.11648/j.ijsd.20160204.14
Downloads:
Views:
Abstract: In India, caste system through economic condition has strong roots in society and it affects the environment in which migration decision takes place. In the present study an attempt has been made to study the trends in rural adult out migration at the household level for different regions to understand the pattern of risk of adult out migration. Some probability models have been proposed to describe the phenomenon and it has been applied to the observed distribution of migrants from the households. Under certain assumptions, it was found that inflated geometric and beta geometric distributions explain satisfactorily the pattern of migration. Also in this study an attempt has been made to know the distribution of risk of migration which cannot be observed directly.
Abstract: In India, caste system through economic condition has strong roots in society and it affects the environment in which migration decision takes place. In the present study an attempt has been made to study the trends in rural adult out migration at the household level for different regions to understand the pattern of risk of adult out migration. So...
Show More
-
Covariates Adaptive Randomization Designs in Clinical Trials: A Comparative Study
Issue:
Volume 2, Issue 4, December 2016
Pages:
72-75
Received:
29 September 2016
Accepted:
24 November 2016
Published:
30 December 2016
DOI:
10.11648/j.ijsd.20160204.15
Downloads:
Views:
Abstract: This paper investigated in covariate adaptive randomization designs, which are used to reduce covariate variables imbalance between treatments in clinical trials. Critical percentage and imbalance minimization methods are compared each one to another, and both are compared with pure randomization method in term of imbalance. The comparison is intended to show which method has minimum imbalance at three covariate variables with twelve single layers and three sample sizes 10, 20 and 100. The results which carried out from the simulation experiment clearly shown that the performance of critical percentage approach is closely similar to imbalance minimization method in full balance case as well as maximum imbalance at all sample sizes. And pure randomization method has the maximum imbalance compared to others at each sample size.
Abstract: This paper investigated in covariate adaptive randomization designs, which are used to reduce covariate variables imbalance between treatments in clinical trials. Critical percentage and imbalance minimization methods are compared each one to another, and both are compared with pure randomization method in term of imbalance. The comparison is inten...
Show More
-
Surveillance Methods for the Rare Health Events-A Systematic Review
Sasikumar Ramaraj,
Bangusha Devi Subramanian
Issue:
Volume 2, Issue 4, December 2016
Pages:
76-80
Received:
3 October 2016
Accepted:
1 November 2016
Published:
30 December 2016
DOI:
10.11648/j.ijsd.20160204.16
Downloads:
Views:
Abstract: In the field of healthscinece, the problem will arise when monitoring the incidence rate of an event is very small. There are only few statistical methods available for the investigation of rare health events. Apart from the first quality control chart introduced by Shewhart, the best well known surveillance procedures are based on the CUSUM method which was used to identify small shift in the process. But this well known surveillance procedure based on Cumulative Sum (CUSUM) method is failed to detect an increased rate when the increased rate of an event is very small. Some of the other methods like Sets method, CUSCORE (Cumulative Score) method and Bernoulli CUSUM method based were developed to carry out this problem. Detailed reviews of these three methods in the field of health science were discussed based on earlier literatures.
Abstract: In the field of healthscinece, the problem will arise when monitoring the incidence rate of an event is very small. There are only few statistical methods available for the investigation of rare health events. Apart from the first quality control chart introduced by Shewhart, the best well known surveillance procedures are based on the CUSUM method...
Show More
