Comparison Between Nelson-Olson Method and Two-Stage Limited Dependent Variables (2SLDV ) Method for the Estimation of a Simultaneous Equations System (Tobit Model)

This study relates to the estimation of a simultaneous equations system for the Tobit model where the dependent variables ( ) are limited, and this will affect the method to choose the good estimator. So, we will use new estimations methods different from the classical methods, which if used in such a case, will produce biased and inconsistent estimators which is (Nelson-Olson) method and Two- Stage limited dependent variables(2SLDV) method to get of estimators that hold characteristics the good estimator . That is , parameters will be estimated for the limited variables and find the variance-covariance matrix for extracted estimators by the aforementioned two methods and then compare between the results of the two methods and find any better method by estimation and then finding the estimation efficiency, and this is what the study aims to . A simultaneous equations system will be imposed for the limited model defined by two equations containing two endogenous variables one of complete observations and the other censored at zero. The two methods were used to analyze the relationship between income and family expenditure on durable consumer goods , where the results showed that the performance of (Nelson-Olson) method is better than performing the Two-Stage limited dependent variables (2SLDV) method in obtain the lower values and all comparison measures as well as the results showed that income and expenditure one affects the other and the and the price affects the income and expenditure

Hausman and Taylor Estimator Analysis on The Linear Data Panel Model

Panel data modelling in the field of econometrics applies two main approaches, namely fixed effect estimators and random effects. The application of the Hausman and Taylor estimator to real data is used to test for fixed effects or random effects based on the idea that the set of estimated coefficients obtained from the fixed effect estimates is taken as a group. A good estimator is an estimator that is as close as possible to represent the characteristics of the population. The characteristics of a good estimator include unbiasedness, efficiency, and consistency. The purpose of this study is to identify the properties of the Hausman and Taylor estimator in the linear model of panel data. Based on the analysis using panel data, it is found that the Hausman and Taylor estimator on the random effects panel data is an estimator that is consistent and efficient even though it is not unbiased.

Direct Seamless Parametrization

We present a method for seamless surface parametrization. Recent popular methods first generate a cross-field, where curvature is concentrated at singular vertices. Next, in a separate step, the surface is laid out in the domain subject to derived seamlessness constraints. This decoupling of the process into two independent problems, each with its own objective, leads to suboptimal results. In contrast, our method solves both problems together using domain variables. The key ingredient to the robustness of our method is a rounding strategy based on local estimation. The insight is that testing a small patch to decide between two likely possibilities is a good estimator. Most distortion measures can be used with our method, which get minimized consistently throughout the pipeline. Our method also enables feature alignment, as well as alignment to principle curvatures, and isotropic and anisotropic scaling.

Evolutionary Manytasking Optimization Based on Symbiosis in Biocoenosis

Evolutionary multitasking is a significant emerging search paradigm that utilizes evolutionary algorithms to concurrently optimize multiple tasks. The multi-factorial evolutionary algorithm renders an effectual realization of evolutionary multitasking on two or three tasks. However, there remains room for improvement on the performance and capability of evolutionary multitasking. Beyond three tasks, this paper proposes a novel framework, called the symbiosis in biocoenosis optimization (SBO), to address evolutionary many-tasking optimization. The SBO leverages the notion of symbiosis in biocoenosis for transferring information and knowledge among different tasks through three major components: 1) transferring information through inter-task individual replacement, 2) measuring symbiosis through intertask paired evaluations, and 3) coordinating the frequency and quantity of transfer based on symbiosis in biocoenosis. The inter-task individual replacement with paired evaluations caters for estimation of symbiosis, while the symbiosis in biocoenosis provides a good estimator of transfer. This study examines the effectiveness and efficiency of the SBO on a suite of many-tasking benchmark problems, designed to deal with 30 tasks simultaneously. The experimental results show that SBO leads to better solutions and faster convergence than the state-of-the-art evolutionary multitasking algorithms. Moreover, the results indicate that SBO is highly capable of identifying the similarity between problems and transferring information appropriately.

Hacer estimaciones estadísticas

Keywords: Estimations, sampling, statisticsAbstract. The notion of statistical estimation both in terms of point and interval is described. The criteria of a good estimator are noted. The procedures to calculate the intervals for the mean, proportions and the difference among two means as well as the confidence intervals for the probable errors in statistics are provided.Palabras clave: Estadística, estimación, muestreoResumen. En la presente investigación se describen la noción de la estimación estadística, tanto de tipo puntual con de forma de intervalo. Se presentan los criterios que debe reunir un estimador bueno. Se notan con ejemplos, la forma de calcular la estimación del intervalo para la media, la proporción y de la diferencia entre dos medias y los intervalos de confianza para los errores probables.

Menguji Konsep Diri Dibidang Akademik Sebagai Variabel Mediator dari Pengaruh Persepsi Atas Keterlibatan Orang Tua Terhadap Hasil Belajar Ekonomi Siswa Kelas XI IPS SMAN Se Kota Malang

Tujuan dari penelitian ini adalah untuk menguji pengaruh persepsi atas keterlibatan orangtua terhadap hasil belajar ekonomi pada siswa SMA, dan untuk menguji apakah konsep diri dibidang akademik berfungsi secara signifikan sebagai variabel mediator pengaruh persepsi keterlibatan orangtua terhadap hasil belajar ekonomi pada siswa SMA. Penelitian ini termasuk jenis penelitian eksplanasi (explanatory research). Penelitian ini merupakan penelitian cross sectional, dimana penelitian ini untuk memperoleh data dari responden pada periode waktu tertentu (data are gathered just once). Populasi dalam penelitian ini adalah seluruh siswa kelas XI Jurusan IPS Tahun Pelajaran 2012/2013 di SMA Negeri di Kota Malang. Penetapan jumlah sampel untuk menjadi responden dalam penelitian ini dilakukan berdasarkan kriteria bahwa sampel memiliki katakteristik estimator yang baik (characteristics of good estimator) dan bermanfaat sebagai penaksir yang baik terhadap populasi Pengambilan sampel sekolah juga memperhatikan sebaran semua SMA Negeri di tiap kecamatan di Kota Malang, yaitu 5 sekolah (50%) berada di Kec. Klojen, 3 sekolah (30%) berada di Kec. Lowokwaru, dan 2 sekolah (20%) berada di Kec. Kedungkandang.Berdasarkan hasil penelitian yang telah dilakukan diperoleh kesimpulan yaitu terdapat pengaruh positif signifikan persepsi atas keterlibatan terhadap hasil belajar ekonomi pada siswa SMAN se Kota Malang, demikain halnya variabel konsep diri dibidang akademik berfungsi secara signifikan sebagai variabel mediator dari pengaruh persepsi keterlibatan orangtua terhadap hasil belajar ekonomi pada siswa SMA. Namun peran variabel konsep diri dibidang akademik dalam model penelitian ini merupakan partial mediation variable atau merupakan variabel yang memediasi sebagian dari pengaruh persepsi atas keterlibatan orang tua terhadap hasil belajar sehingga ada variable lain yang juga turut memediasi hubungan kausal tersebut yang tidak diteliti dalam model iniKata Kunci : Konsep diri, keterlibatan orang tua, hasil belajar,

Statistical correlation properties of the SHIBOR interbank lending market

Purpose – The purpose of this paper is to investigate the statistical correlation properties of the Shanghai Interbank Offered Rate (SHIBOR) interbank lending market. Design/methodology/approach – The authors apply methods of correlation analysis, random matrix theory (RMT) and minimum spanning tree (MST) to investigate the correlation properties of Chinese interbank lending market and analyze how the SHIBOR panel banks behave in different market periods. Findings – First, the largest eigenvalue λ 1 is the index to describe the market mode of the whole market when all banks behavior collectively and λ 1/N is a good estimator of the average correlation <C> of the correlation matrix. Second, notably, the authors find the “market mode” is weakened in two crises periods of 2008 stock market crash and 2009 Global Financial Crisis. This is significantly different from other market where the “market mode” is normally strengthened in crises periods. Third, the authors subtract the contribution of λ 1, the second and third eigenvalue, λ 2 and λ 3, will fall outside of the predicted interval. And both λ 2 and λ 3 are getting times larger in the crises periods than in “Non-Crisis” period. Fourth, and in the MST analysis, the authors find again that the average distances of the MST are the times larger in crises periods than in “Non-Crisis” period and the second largest eigenvalue is a good estimator of the average distance of the MST. Originality/value – According to the best knowledge, this paper is the first work on the study of the statistical properties of an interbank lending market using quotation level data of panel banks, which allows us to analyze the properties of the interest rate formation and how all panel banks behavior in different periods. This work is also the first study on the SHIBOR market using econophysics methods of correlation analysis, RMT and MST.

14C Dating of Cremated Bones: The Issue of Sample Contamination

Recent comparative studies have proven the validity of radiocarbon dates of cremated bones. The issue of sample contamination has, however, been overlooked in most studies. Analyses of cremated bone samples has shown that in some cases, cremated bones are contaminated. This contamination is more distinct near the surface of the bones and depends on the compactness of the cremated bone as well as on the site conditions. δ13C is not a good estimator to discriminate between contaminated and uncontaminated bones. An acetic acid pretreatment is the most appropriate method to clean samples, but it is better to remove the surface and to avoid cremated bones that are not entirely white (cremation temp. <725 °).

On the Post Hoc Power in Testing Mean Differences

Retrospective or post hoc power analysis is recommended by reviewers and editors of many journals. Little literature has been found that gave a serious study of the post hoc power. When the sample size is large, the observed effect size is a good estimator of the true effect size. One would hope that the post hoc power is also a good estimator of the true power. This article studies whether such a power estimator provides valuable information about the true power. Using analytical, numerical, and Monte Carlo approaches, our results show that the estimated power does not provide useful information when the true power is small. It is almost always a biased estimator of the true power. The bias can be negative or positive. Large sample size alone does not guarantee the post hoc power to be a good estimator of the true power. Actually, when the population variance is known, the cumulative distribution function of the post hoc power is solely a function of the population power. This distribution is uniform when the true power equals 0.5 and highly skewed when the true power is near 0 or 1. When the population variance is unknown, the post hoc power behaves essentially the same as when the variance is known.