Analisis Pola Pertumbuhan dan Morfometrik Udang Jerbung (Penaeus merguiensis De Man, 1888) di Perairan Sekitar Bakoi, Sorong Selatan

The waters of South Sorong have potential shrimp resources, including abundant banana shrimp (Penaeus merguiensis de Man, 1888). This study aims to obtain information about the morphometric characteristics and growth of banana shrimp in the fishing area around the waters of Kampung Bakoi, South Sorong Regency, West Papua Province. Data collections were carried out in June and October 2019 using descriptive methods with direct observation techniques. Based on the results of data analysis, it was found that the total length of shrimp caught in Bakoi Village was in the range of 10 - 26.8 cm and the most were caught measuring 15.2 cm to 16.4 cm. The model of the relationship between length and weight of banana shrimp in Bakoi Village follows the equation Log W= 1,630+2,659 Log (L) or the form of negative allometric growth. Analysis of the relationship between total length (Y) and carapace length (X) (including rostrum) and the relationship between total length and carapace length (Z) (excluding rostrum) obtained the best estimator models, each following the logarithmic equations L = -2,188 + 10,226 Ln(PK) and L = 4,439 + 9,201 Ln(PKt) respectively.

ANALISIS SURVIVAL UNTUK PARAMETER SKALA DARI DISTRIBUSI WEIBULL MENGGUNAKAN MLE DAN METODE BAYESIAN

Modeling of survival data is necessary and important to do. Survival data is generally assumed to have a Weibull distribution. Bayesian approach has been implemented to estimate the parameter in such this survival analysis. This study purposes to compare the performance of the Maximum Likelihood and Bayesian using Invers Gamma as prior conjugate for estimating the survival function of scale parameter of Weibull distribution. The comparisons are made through simulation study. The best performance of both estimators is chosen based on the lowest value of absolute bias and the mean square error. Two different size samples are generated to illustrate the life time data which are used in this study. This study results that maximum likelihood is the best estimator compared to Bayes with Invers Gamma distribution as conjugate prior.

Reliability of (1+1) Cascade Model for Weibull Distribution

This study present derives the formula mathematical for reliability cascade model (1+1) for Weibull distribution. Model reliability expressions obtained when Weibull random variables are stress and strength distributions. The ML, Pr, and LS methods estimated the model reliability and used for the comparison between them in simulation with MATLAB using criterion MSE. The comparison indicated that the best estimator was the ML method.

Estimating the Reliability Function of some Stress- Strength Models for the Generalized Inverted Kumaraswamy Distribution

This paper discusses reliability of the stress-strength model. The reliability functions 𝑅1 and 𝑅2 were obtained for a component which has an independent strength and is exposed to two and three stresses, respectively. We used the generalized inverted Kumaraswamy distribution GIKD with unknown shape parameter as well as known shape and scale parameters. The parameters were estimated from the stress- strength models, while the reliabilities 𝑅1, 𝑅2 were estimated by three methods, namely the Maximum Likelihood, Least Square, and Regression. A numerical simulation study a comparison between the three estimators by mean square error is performed. It is found that best estimator between the three estimators is Maximum likelihood estimators.

PENGUJIAN HIPOTESIS SIMULTAN MODEL REGRESI NONPARAMETRIK SPLINE TRUNCATED DALAM PEMODELAN KASUS EKONOMI

The pattern in a relationship between the response variable and the predictor variable can be known and some cannot be known. In determining the unknown pattern of relationships, nonparametric regression approaches can be used. The nonparametric regression approach is very flexible. One of the most frequently used nonparametric regression approaches is the truncated spline. Truncated splines are polynomial pieces that are segmented and continuous. The purpose of this study is to obtain the best estimator model in the Gini Ratio case against the variables suspected of influencing it, then perform simultaneous hypothesis testing on the nonparametric regression model. The criteria for the goodness of the model use the GCV and R2 values. In the case modeling of the District / City Gini Ratio in East Java Province using a nonparametric regression approach, it was found that the truncated spline estimator with 3 knots points gave quite good results. This is indicated by the coefficient of determination of the truncated spline estimator, which is 84.76%. Based on the results of simultaneous testing, it was found that the open unemployment rate, the percentage of poor people and the rate of economic growth simultaneously had an influence on the Gini Ratio.

Temporal variation and ecological parameters of hawkmoths (Lepidoptera: Sphingidae) in savannahs in the Alter do Chão protection area, Santarém, Pará, Brazil

This study evaluated the seasonality of Sphingidae spp. in two areas of savannah, in the eastern Brazilian Amazon, sampled for one year (June, 2014 through May, 2015) with the aid of Pennsylvania light traps placed at four sampling points. Data on fauna were obtained through the following parameters: abundance (N), richness (S), composition, Shannon diversity and uniformity indices (H’ and U’), and the Berger-Parker (BP) dominance index. Richness estimates were calculated using Bootstrap, Chao1, ACE, Jackknife 1, and Jackknife2 estimators. The Pearson correlation was also used to analyze the effect of climatic variables such as rainfall, temperature, and relative humidity on richness and abundance. The result for the parameters analyzed during the entire sampling period was N= 374, S= 34, H’= 2.59, U= 0.733 and BP= 0.235. The estimation of richness showed that between 63% and 87% of expected species were collected (Bootstrap estimated 39 species and Chao1 estimated 54). The most representative species were: Isognathus caricae (Linnaeus, 1758) (N= 88), Enyo lugubris lugubris (Linnaeus, 1771) (N= 58), Isognathus menechus (Boisduval, [1875]) (N= 46) and Cocytius duponchel (Poey, 1832) (N= 44), with 54% of the sample containing species considered rare divided into 298 male and 76 female specimens. For climatic variables, there was a moderate positive correlation only between abundance and temperature. The less-rainy period presented greater richness (S= 26) and abundance (N= 222), and the rainy period had better indices for H’ (2.55), U (8.01), and BP (0.230). The richness estimator Jackknife 2 was the best estimator in both sampling periods with 34 in the less-rainy period and 45 in the rainy period. The richness and abundance obtained in this study contribute significantly to the knowledge of Sphingidae fauna in an area of Amazonian savannahs.

Bayesian inference for Pareto distribution with prior conjugate and prior non conjugate

The purpose of this study is to determine the best estimator for estimating the shape parameters of the Pareto distribution with the known scale parameter. Estimation of these parameters is done by using the Gamma distribution as the prior distribution of the conjugate and the Uniform distribution as the non-conjugate prior distribution. A comparison of the two prior distributions is done through simulation studies with various sample sizes. The best estimator net is a method that produces the smallest posterior variance, absolute bias, and Bayes confidence interval. This study proves that the Bayes estimator by using the prior conjugate distribution produces all indicators of the goodness of the model with a smaller value than the non-conjugate prior distribution. Thus it can be concluded that the estimator with prior conjugate will produce a better predictive value than prior non-conjugate.

Understanding German FDI in Latin America and Asia: A Comparison of GLM Estimators

The growth of Foreign Direct Investment (FDI) in developing countries over the last decade has attracted an intense academic and policy-oriented interest for its determinants. Despite the gravity model being considered a useful tool to approximate bilateral FDI flows, the literature has seen a growing debate in relation to its econometric specification, so that which is the best estimator for the gravity equation is far from conclusive. This paper examines the determinants of German outward FDI in Latin America and Asia for the period 1996-2012 by evaluating the performance of alternative Generalized Linear Model (GLM) estimators. Our findings indicate that Negative Binomial Pseudo Maximum Likelihood (NBPML) is the estimator best matched to our data, followed by Gamma Pseudo Maximum Likelihood (GPML). Furthermore, German FDI in Latin America is found to be predominantly vertical in nature, whereas that in Asia is mainly market-seeking.

Comparison of simplified techniques for solving selected coupled electroheat problems

Purpose The purpose of this paper is to compare different reduced-order models for models of control of induction brazing process. In the presented application, the problem is to reconstruct temperature at the points of interests (hot spots) from information measured at accessible places. Design/methodology/approach The paper describes the process of induction brazing. It presents the full field model and evaluates the possibilities for obtaining reduced models for temperature estimation. The primary attention is paid to the model based on proper orthogonal decomposition (POD). Findings The paper shows that for the given application, it is possible to find low-order estimator. In the examined linear case, the best estimator was created using POD reduced model together with the linear Kalman filter. Research limitations/implications The authors are aware of two main limitations of the presented study: material properties are considered linear, which is not a completely realistic assumption. However, if strong coupling and nonlinear material parameters are considered, the model becomes unsolvable. The process and measurement uncertainties are not considered. Originality/value The paper deals with POD of multi-physics 3 D application of induction brazing. The paper compares 11 different methods for temperature estimator design.

Comparison of Two Priors in Bayesian Estimation for Parameter of Weibull Distribution

This present study purposes to conduct Bayesian inference for scale parameters, denoted by , from Weibull distribution. The prior distribution chosen in this study is the prior conjugate, that is inverse gamma and non-informative prior, namely Jeffreys’ prior. This research also aims to study several theoretical properties of posterior distribution based on prior used and then implement it to generated data and make comparison between both Bayes estimator as well. The method used to evaluate the best estimator is based on the smallest Mean Square Error (MSE). This study proved that Bayes estimator using conjugate prior produces parameter value that is better estimate than the non-informative prior since it produces smaller MSE value, for condition scale parameter value more than one based on analytic and simulation study. Meanwhile for scale parameter value less than one, it could not yielded the good estimated value.