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On the Construction of Trend Free Run Order of the Two-Level Factorial Design Using BIBD
Puja Thapliyal,
Veena Budhraja
Issue:
Volume 9, Issue 6, November 2020
Pages:
263-266
Received:
28 September 2020
Accepted:
19 October 2020
Published:
30 October 2020
Abstract: Randomization is one of the powerful tools to analyze, construct and draw valid and unbiased conclusions about the factorial design. But in some experimental situations, the technique may not perform equally well to draw valid inferences. These situations may arise due to an influence of external variations like the ageing of catalyst, known as Time-trend or Trend, on the response. Thus, instead of randomizing the run order of the factorial design, systematically arranging the order of treatments that is free of variations, neutralizes the adverse effect of Trend. Such systematic designs are known as Trend Free designs. The design gives not only higher importance to the treatments but also ensures the independence of treatments for further analysis. Methods for constructing trend-free run order of two-level designs have been studied and developed by many authors. The proposed run order for 2k and 2k-p design that are linear and quadratic trend free. Systematic run order has been constructed not only to eliminate the effect of the linear and quadratic trend but also to improve design performance in the presence of a trend. This article provides another technique to develop trend free run order of two-level factorial design using Symmetric Balanced Incomplete Block Design.
Abstract: Randomization is one of the powerful tools to analyze, construct and draw valid and unbiased conclusions about the factorial design. But in some experimental situations, the technique may not perform equally well to draw valid inferences. These situations may arise due to an influence of external variations like the ageing of catalyst, known as Tim...
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Measuring the Socio-economic Status of Adopters of Indigenous Chicken in Mwala and Machakos Central, Kenya: Application of Principal Component Analysis
Ngetich Titus,
Karanjah Anthony,
Cheruiyot Kipkoech
Issue:
Volume 9, Issue 6, November 2020
Pages:
267-271
Received:
27 September 2020
Accepted:
24 October 2020
Published:
4 November 2020
Abstract: This study focused on impact assessment of indigenous Chicken (KALRO Improved Chicken) in terms of the Socio-economic Status of the beneficiaries. Data analyzed comprised of household assets owned and housing characteristics. Studies have been done to assess the impact of new agricultural technologies to the beneficiaries, however, the measurement of the impact indicator (Socio-economic Status) has been a challenge. Studies rely on monetary data (reported income and expenditure), however the collection of high quality (precise and accurate) income data and expenditure is difficult and requires more resources particularly for household surveys, this approach is usually affected by unreliable reportage and measurement error, high-quality income data and expenditure will still produce biased estimates of household socio-economic status because they measure economic flows which are stochastic and include temporary income shocks. This study used principal component analysis model (PCA) to create an asset index to measure Socio-economic status. It was concluded that PCA is reliable in creating an asset index for measuring Socio-economic status, the results showed that about 40% of the households in Machakos County were poor which implies a small decline compared to 42.6% reported on [11] conducted by Kenya National Bureau of Statistics.
Abstract: This study focused on impact assessment of indigenous Chicken (KALRO Improved Chicken) in terms of the Socio-economic Status of the beneficiaries. Data analyzed comprised of household assets owned and housing characteristics. Studies have been done to assess the impact of new agricultural technologies to the beneficiaries, however, the measurement ...
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Exponentiated Rayleigh Poisson Distribution: Model, Properties and Applications
Ramesh Kumar Joshi,
Govinda Prasad Dhungana
Issue:
Volume 9, Issue 6, November 2020
Pages:
272-282
Received:
6 October 2020
Accepted:
24 October 2020
Published:
4 November 2020
Abstract: In this research paper, a new class of life-time distribution is introduced by compounding A new generalization of Rayleigh distribution; properties and applications and The Exponentiated G Poisson model, the so-called Exponentiated Rayleigh Poisson distribution. Main aim of this research article is to enhance the flexibility of Exponentiated G. Poisson distribution by power transformation technique. The probability density function, the survival function and the hazard function of the new proposed model in graphical form are illustrated. We study the properties of this new distribution with special emphasis on its quantile function, mode, skewness, kurtosis and moments. We have discussed residual life function, the probability-weighted moments, order statistics, R'enyi and entropies. We also discussed parameter estimation considering the maximum likelihood estimation approach. We have calculated the value of log-likelihood, Akaike's information criteria, Bayesian information criteria, corrected Akaike's information criteria and Hennan-Quinn information criteria of Generalized Rayleigh distribution, Exponentiated Chen distribution, Exponentiated Exponential distribution, Exponentiated Inverted Weibull distribution, Compound Rayleigh distribution and newly proposed Exponentiated Rayleigh Poisson distribution and found that the newly proposed model has smaller values in comparison to other. We have studied the P-P plot, Q-Q plot Kolmogorov Smirnov test and TTT plot of the proposed distribution for model validation. We compared the empirical distribution CDF and estimated distributed function CDF of the proposed model with five other models. A real dataset is analyzed for illustrative purposes. The importance and flexibility of the new family is illustrated by applying different techniques and tools. A final conclusion concludes the paper.
Abstract: In this research paper, a new class of life-time distribution is introduced by compounding A new generalization of Rayleigh distribution; properties and applications and The Exponentiated G Poisson model, the so-called Exponentiated Rayleigh Poisson distribution. Main aim of this research article is to enhance the flexibility of Exponentiated G. Po...
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On the Analysis and Modelling of the Harmonized Consumer Price Indices of West African Economic and Monetary Union Member States
Joseph Koula,
Tagouelbe Tiho,
Adasse Christophe Chiapo
Issue:
Volume 9, Issue 6, November 2020
Pages:
283-295
Received:
23 October 2020
Accepted:
6 November 2020
Published:
19 November 2020
Abstract: The major goal of this paper is a better understanding of the price dynamics of the eight West African Economic and Monetary Union (WAEMU) member states. More specifically, the study intends to find the best models with suitable forecasting power for the monthly Harmonized Consumer Price Indices (HCPI) of each of the WAEMU countries. Descriptive statistics and time series modeling approaches were applied to the HCPI base 100=2008 series covering the period from January 1998 to December 2019. The analysis revealed that Guinea-Bissau had the highest average HCPI of 99.88 and Senegal the lowest of 93.73. Togo attained the highest HCPI of 119.60 and Benin the lowest of 71.54 over the period studied. The indices of Togo and Guinea-Bissau have the highest and the smallest variance of 225.56 and 79.60, respectively. All the indices have an upward trend and contain cyclical and seasonal components. Using the Box-Jenkins methodology and Expert Modeler of SPSS five types of outliers, i.e. additive, additive patch, transient, innovational and level change, have been detected and different SARIMA models were proposed. Bartlett's B-test detects significant periodic effects in the residuals of the models for Burkina-Faso and Côte d’Ivoire. The residuals of all the models have been declared Gaussian by Shapiro-Wilks and Jarque-Bera normality tests while those of Côte d’Ivoire fail the latest test for normality due to the discrepancy of their skewness with that of a normal distribution. Adequacy of the claimed models has been corroborated by adequate values of key fitting and predicting statistics and the non-significance of the paired t-test on the mean difference between the observed and the adjusted values. Thus SARIMA (0,1,0) (0,1,1)12 model was found to best fit the HCPI for Burkina Faso, Côte d'Ivoire, Niger, Senegal and Togo; and the data for Benin, Guinea Bissau and Mali are found to be SARIMA (3,1,0) (1,0,1)12, SARIMA (0,1,0) (1,0,1)12 and SARIMA (1,1,1) (0,1,1)12 process, respectively. The differences between the retained models raise doubts on the claimed objective of convergence of the economies of the WAEMU countries. Engle's Lagrange Multiplier test for autoregressive conditional heteroscedasticity (ARCH) reveals the homoscedasticity of the residuals of all the models but the one of Côte d'Ivoire. Thus, for better modeling of the index of Côte d’Ivoire, a GARCH model may be envisioned.
Abstract: The major goal of this paper is a better understanding of the price dynamics of the eight West African Economic and Monetary Union (WAEMU) member states. More specifically, the study intends to find the best models with suitable forecasting power for the monthly Harmonized Consumer Price Indices (HCPI) of each of the WAEMU countries. Descriptive st...
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Analysis of Tea Auction Prices Using Non-Cointegration Based Techniques
Hilda Chepkosgei Rotich,
Joel Cheruiyot Chelule,
Herbert Imboga
Issue:
Volume 9, Issue 6, November 2020
Pages:
296-305
Received:
29 October 2020
Accepted:
10 November 2020
Published:
27 November 2020
Abstract: Favorable product prices act as a set off for any commercial activity normally and perhaps its sustainability. Tea is a significant commercial crop in Kenya and has contributed immensely to the economy’s Gross Domestic Product (GDP) through its export earnings. However, tea industry has gone through many phases of ups and downs, particularly in terms of its export performance recently. Therefore, there is need to study the behavior of tea auction prices to get a deeper perspective into the behavior of the tea prices and to develop a model that is suitable to forecast the tea auction prices precisely. The study aimed at analyzing the trend of tea auction prices in Kenya, fit a suitable model for forecasting tea auction prices and finally, forecast the future tea prices using the most optimal model. The findings of this study will therefore inform the government and other policy makers in terms of its policy formulation regarding the tea sector in order to accord it a competitive position in the global arena. The study used univariate and multivariate forecasting techniques which do not impose co-integration restrictions such as the Autoregressive Integrated Moving Average (ARIMA) and the Vector Autoregressive (VAR). The techniques used were chosen because of their flexibility, wide acceptability and they are also easy to utilize. The study used secondary data for the Mombasa Tea Auction Centre for a period of 2009 to 2018. Augmented Dicker-Fuller (ADF) test was performed for unit root tests to check for stationary of the price series. ACF and PACF functions were estimated to assist in deciding the most appropriate orders of AR (p) and MA (q) models. AIC test was used because were considering several ARIMA models and the model with the lowest AIC was chosen. VAR model showed a high forecasting error with MAPE of 85.64% compared to that ARIMA of 9.2% for tea prices. ARIMA model performed much better than VAR model because of its high forecasting accuracy.
Abstract: Favorable product prices act as a set off for any commercial activity normally and perhaps its sustainability. Tea is a significant commercial crop in Kenya and has contributed immensely to the economy’s Gross Domestic Product (GDP) through its export earnings. However, tea industry has gone through many phases of ups and downs, particularly in ter...
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Calculus Optimum Values Optimality Criteria for Twenty Four Points Specific Second Order Rotatable Design in Three Dimensions
Kiplagat Nicholas Kipkosgei,
Mutiso John Muindi,
Rambaei Keny Silver Jeptoo
Issue:
Volume 9, Issue 6, November 2020
Pages:
306-311
Received:
10 June 2020
Accepted:
7 July 2020
Published:
22 December 2020
Abstract: This study uses the existing second order rotatable design to obtain optimum design based on the known classical optimality criteria that is the determinant criterion, the average-variance criterion, the smallest-Eigen value criterion and the trace criterion. These criteria measure the desirability of a design, D-optimum design minimizes the content of the ellipsoidal confidence region for the parameters of the linear model, A-optimum design minimizes the sum (or average) of the variances of the parameter estimates, E-criterion reduces the variance of each individual parameter estimate and T-criterion is one that has not enjoyed much use because of the linearity aspect of T-criterion. This study considers the already existing twenty four points three dimensional specific rotatable design of order two. The information matrices C1, for this design is obtained from the moment matrix M, for the second order model for three factors using the relation C=(K1M-1K)-1, where M=1/N(X1X), is the moment matrix, K is the coefficient matrix of the parameter sub system of interest. Our parameter system of interest is that of the linear and pure quadratic factors only. The optimality criteria for the design with the corresponding information matrix C1, is determined as A-optimal.
Abstract: This study uses the existing second order rotatable design to obtain optimum design based on the known classical optimality criteria that is the determinant criterion, the average-variance criterion, the smallest-Eigen value criterion and the trace criterion. These criteria measure the desirability of a design, D-optimum design minimizes the conten...
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Predicting Chlamydia Trachomatis Infection in a Mining Community in Western Ghana
Christiana Cynthia Nyarko,
Nicholas Nicodemus Nana Nsowah-Nuamah,
Mettle Felix Oko,
Peter Kwesi Nyarko
Issue:
Volume 9, Issue 6, November 2020
Pages:
312-318
Received:
7 October 2020
Accepted:
6 November 2020
Published:
22 December 2020
Abstract: Chlamydia Trachomatis (CT) infection among females in a mining community in Western Ghana is a major medical issue. Screening using laboratory test results have been the usual control and prevention of STI globally but have been found to have its own limitations due to delay in test results leading to further transmission of genital infections. Consequently, a statistical model is formulated to predict the incidence of Chlamydia Trachomatis (CT) infection among females in the community. The model used a Modified Univariate Normal Discriminant Function, a Logistic Regression Model and specific symptoms associated with Chlamydial infection as part of the explanatory variables. Samples were taken from 186 patients consisting of 40 males and 146 females from two hospitals in the Tarkwa Nsuaem Municipality, a mining community in Western Ghana. The model was validated using a sensitivity analysis test and Apparent Error Rate (APER). The model predicted decreasing infection rate of patients with increasing age. The most reported and significant symptoms among the female patients diagnosed was vaginal discharge, (p<0.05). The study predicted a patient as positive or infected with Chlamydial, if the result of the model evaluated gave a positive value, otherwise the patient was declared free of infection. Further analysis of the proposed Statistical Chlamydia Trachomatis (SCT) model gave a sensitivity of 84% which was consistent with other research findings like the rapid point of care (POC) diagnostic test for Chlamydial infection with sensitivity range of 55–85% for high prevalence populations. The study observed that young females in mining communities are at risk of acquiring Chlamydial T infection if presenting with vaginal discharge. Identifying these risk factors associated with Chlamydial infection among young women in the mining communities would help inform health care officials the rate of infection in the Municipality, and accordingly mount public educational health campaign in the Municipality aimed at minimizing the spread of chlamydial infections and any other STI.
Abstract: Chlamydia Trachomatis (CT) infection among females in a mining community in Western Ghana is a major medical issue. Screening using laboratory test results have been the usual control and prevention of STI globally but have been found to have its own limitations due to delay in test results leading to further transmission of genital infections. Con...
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