scholarly journals A simple non-parametric goodness-of-fit test for elliptical copulas

2017 ◽  
Vol 5 (1) ◽  
pp. 330-353 ◽  
Author(s):  
Miriam Jaser ◽  
Stephan Haug ◽  
Aleksey Min
Keyword(s):  
Monte Carlo ◽  
Goodness Of Fit ◽  
Monte Carlo Study ◽  
Goodness Of Fit Test ◽  
Kendall’S Tau ◽  
Kendall's Tau ◽  
Nominal Level ◽  
Empirical Application ◽  
Non Parametric

AbstractIn this paper, we propose a simple non-parametric goodness-of-fit test for elliptical copulas of any dimension. It is based on the equality of Kendall’s tau and Blomqvist’s beta for all bivariate margins. Nominal level and power of the proposed test are investigated in a Monte Carlo study. An empirical application illustrates our goodness-of-fit test at work.

A test for fuzzy exponentiality based on Kullback-Leibler information

2021 ◽  
pp. 1-8
Author(s):  
Lingtao Kong
Keyword(s):  
Biological Sciences ◽  
Monte Carlo ◽  
Goodness Of Fit ◽  
Experimental Studies ◽  
Real Data ◽  
Test Statistics ◽  
Test Statistic ◽  
Goodness Of Fit Test ◽  
Higher Power ◽  
Leibler Information

The exponential distribution has been widely used in engineering, social and biological sciences. In this paper, we propose a new goodness-of-fit test for fuzzy exponentiality using α-pessimistic value. The test statistics is established based on Kullback-Leibler information. By using Monte Carlo method, we obtain the empirical critical points of the test statistic at four different significant levels. To evaluate the performance of the proposed test, we compare it with four commonly used tests through some simulations. Experimental studies show that the proposed test has higher power than other tests in most cases. In particular, for the uniform and linear failure rate alternatives, our method has the best performance. A real data example is investigated to show the application of our test.

scholarly journals Are hemoglobin and volume oxygen maximum (vo2max) relevant each other?

2021 ◽  
Vol 6 (2) ◽  
pp. 193-200
Author(s):  
Isti Dwi Puspita Wati
Keyword(s):  
Carbon Dioxide ◽  
Parametric Analysis ◽  
Respiratory Cycle ◽  
Correlational Study ◽  
Table Tennis ◽  
Kendall’S Tau ◽  
Kendall's Tau ◽  
Close Relationship ◽  
Carbon Dioxide Co2 ◽  
Non Parametric

The support for recording achievements in sports achievements, two of which are the ability to enter oxygen (O2) into the lungs and further the ability to take up this oxygen so that it can be utilized in the process of providing energy. The second function of O2 is to transport carbon dioxide (CO2) through respiration. These two processes are carried out simultaneously at least between the respiratory cycle and its close relationship with hemoglobin. Hemoglobin is part of the blood which has a function to bind O2 and CO2 at the end in the process of respiration. The purpose of this study was to determine evidence of a relationship between HB and VO2max. This research is a descriptive correlational study. Samples are sports athletes who are preparing for Pre PAPUA. The number of samples was 83 athletes in the game group consisting of sand volleyball (6), badminton (17), Petanque (12), table tennis (13), and Futsal (35). Measurement of VO2max was done by using the Bleep test and HB with the Hb test. Based on Kendall's tau non-parametric analysis, it is found that HB and VO2max are sufficiently correlated, so it is not certain that the higher the HB the higher the VO2max, although in the process of supplying energy these two variables are mutually supportive and relate.

scholarly journals Analisis Prediksi IHSG Berdasarkan Kurs Beli IDR-USD Melalui Regresi Copula

d'CARTESIAN ◽  
2018 ◽  
Vol 7 (2) ◽  
pp. 59
Author(s):  
Nia Lestari Arisandi ◽  
Didit Budi Nugroho ◽  
Leopoldus Ricky Sasongko
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Model ◽  
Normal Model ◽  
Marginal Return ◽  
Kendall’S Tau ◽  
Kendall's Tau ◽  
Spearman's Rho ◽  
Spearman’S Rho

Analisis prediksi merupakan langkah penting yang perlu dilakukan untuk menganalisis suatu model prediksi. Suatu model prediksi ditentukan untuk suatu tujuan guna memperoleh perkiraan nilai dari suatu pengamatan di masa depan. Pada umumnya, model prediksi diperoleh melalui metode regresi. Dalam paper ini, model prediksi yang dibahas adalah model yang diperoleh melalui metode regresi dan yang melibatkan fungsi yang disebut copula (bivariat), yang kemudian model ini disebut model regresi copula. Copula merupakan suatu fungsi distribusi gabungan yang dapat digunakan untuk menganalisis kebergantungan peubah-peubah acak dalam struktur yang digambarkan oleh fungsi copula itu sendiri. Fungsi-fungsi copula yang variatif mampu memberikan banyak pilihan model-model regresi copula. Data yang dikaji dalam paper ini adalah data return IHSG dan return Kurs Beli IDR-USD, yang kemudian kedua data tersebut dimodelkan melalui model regresi copula. Ukuran kebergantungan kedua data return dapat dinyatakan oleh Kendall’s Tau dan Spearman’s Rho. Parameter yang dimiliki copula diestimasi melalui nilai Kendall’s Tau atau Spearman’s Rho yang diperoleh dari kedua data return sehingga tiap copula memiliki kemungkinan untuk memodelkan kedua data return berdasarkan parameter yang telah diestimasi dari cara tersebut. Model regresi copula diperoleh dari ekspektasi bersyarat yang dimiliki copula untuk peubah return IHSG bergantung pada peubah return Kurs Beli IDR-USD yang mana perolehan nilai prediksi return IHSG yang bergantung pada nilai return Kurs Beli IDR-USD dihitung dengan menggunakan metode Monte Carlo. Model regresi copula terbaik dari hasil pembahasan dalam paper ini adalah model regresi copula Frank dengan distribusi marginal return IHSG adalah distribusi Laplace dan marginal return Kurs beli IDR-USD adalah distribusi Normal. Model regresi copula Frank tersebut terpilih menjadi yang terbaik berdasarkan dari error nilai prediksi terhadap data return IHSG yang bergantung pada return Kurs Beli IDR-USD relatif kecil dibandingkan dengan model regresi copula lain yang dibahas dalam paper ini.Kata Kunci :  Prediksi, Copula, Ukuran Kebergantungan, Kurs dan IHSG, Monte Carlo 

A monte carlo method for foutz's goodness-of-fit test

1988 ◽  
Vol 29 (4) ◽  
pp. 309-316 ◽  
Author(s):  
Myoungshic Jhun ◽  
Pui Lam Leung
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Goodness Of Fit ◽  
Goodness Of Fit Test

scholarly journals Goodness-of-fit test of multivariate t-distribution with Monte Carlo simulation using R

2018 ◽  
Author(s):  
Ibnu Santoso ◽  
Tiodora Hadumaon Siagian ◽  
Erni Tri Astuti ◽  
Azka Ubaidillah
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Goodness Of Fit ◽  
Goodness Of Fit Test ◽  
Multivariate T Distribution ◽  
T Distribution ◽  
Multivariate T
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