• 제목/요약/키워드: Ratio of random variable

검색결과 78건 처리시간 0.017초

Reliability in Two Independent Uniform and Power Function-Half Normal Distribution

  • Woo, Jung-Soo
    • Communications for Statistical Applications and Methods
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    • 제15권3호
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    • pp.325-332
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    • 2008
  • We consider estimation of reliability P(Y < X) and distribution of the ratio when X and Y are independent uniform random variable and power function random variable, respectively and also consider the estimation problem when X and Y are independent uniform random variable and a half-normal random variable, respectively.

Variance estimation for distribution rate in stratified cluster sampling with missing values

  • Heo, Sunyeong
    • Journal of the Korean Data and Information Science Society
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    • 제28권2호
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    • pp.443-449
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    • 2017
  • Estimation of population proportion like the distribution rate of LED TV and the prevalence of a disease are often estimated based on survey sample data. Population proportion is generally considered as a special form of population mean. In complex sampling like stratified multistage sampling with unequal probability sampling, the denominator of mean may be random variable and it is estimated like ratio estimator. In this research, we examined the estimation of distribution rate based on stratified multistage sampling, and determined some numerical outcomes using stratified random sample data with about 25% of missing observations. In the data used for this research, the survey weight was determined by deterministic way. So, the weights are not random variable, and the population distribution rate and its variance estimator can be estimated like population mean estimation. When the weights are not random variable, if one estimates the variance of proportion estimator using ratio method, then the variances may be inflated. Therefore, in estimating variance for population proportion, we need to examine the structure of data and survey design before making any decision for estimation methods.

An importance sampling for a function of a multivariate random variable

  • Jae-Yeol Park;Hee-Geon Kang;Sunggon Kim
    • Communications for Statistical Applications and Methods
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    • 제31권1호
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    • pp.65-85
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    • 2024
  • The tail probability of a function of a multivariate random variable is not easy to estimate by the crude Monte Carlo simulation. When the occurrence of the function value over a threshold is rare, the accurate estimation of the corresponding probability requires a huge number of samples. When the explicit form of the cumulative distribution function of each component of the variable is known, the inverse transform likelihood ratio method is directly applicable scheme to estimate the tail probability efficiently. The method is a type of the importance sampling and its efficiency depends on the selection of the importance sampling distribution. When the cumulative distribution of the multivariate random variable is represented by a copula and its marginal distributions, we develop an iterative algorithm to find the optimal importance sampling distribution, and show the convergence of the algorithm. The performance of the proposed scheme is compared with the crude Monte Carlo simulation numerically.

Notes on the Ratio and the Right-Tail Probability in a Log-Laplace Distribution

  • Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제18권4호
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    • pp.1171-1177
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    • 2007
  • We consider estimation of the right-tail probability in a log-Laplace random variable, As we derive the density of ratio of two independent log-Laplace random variables, the k-th moment of the ratio is represented by a special mathematical function. and hence variance of the ratio can be represented by a psi-function.

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THE GENERALIZED RATIO-OF-UNIFORM METHOD

  • Chung, Youn-Shik;Lee, Sang-Jeen
    • Journal of applied mathematics & informatics
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    • 제4권2호
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    • pp.469-476
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    • 1997
  • In this paper we present a random number generation method which is one of the rejection methods, To accelerate ratio-of-uniform method we use an efficiency variable γ. After finding the optimal value of γwith respect to interesting distribution with pro-portional density random numbers can be generated in acceleration.

Reducing the PAPR of OFDM Systems by Random Variable Transformation

  • Taher, Montadar Abas;Singh, Mandeep Jit;Ismail, Mahamod Bin;Samad, Salina Abdul;Islam, Mohammad Tariqul
    • ETRI Journal
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    • 제35권4호
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    • pp.714-717
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    • 2013
  • Peak power reduction techniques in orthogonal frequency division multiplexing (OFDM) has been an important subject for many researchers for over 20 years. In this letter, we propose a side-information-free technique that is based on the concept of random variable (RV) transformation. The suggested method transforms RVs into other RVs, aiming to reshape the constellation that will consequently produce OFDM symbols with a reduced peak-to-average power ratio. The proposed method has no limitation on the mapping type or the mapping order and has no significant effect on the bit error rate performance compared to other methods presented in the literature. Additionally, the computational complexity does not increase.

Asymptotic Test for Dimensionality in Probabilistic Principal Component Analysis with Missing Values

  • Park, Chong-sun
    • Communications for Statistical Applications and Methods
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    • 제11권1호
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    • pp.49-58
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    • 2004
  • In this talk we proposed an asymptotic test for dimensionality in the latent variable model for probabilistic principal component analysis with missing values at random. Proposed algorithm is a sequential likelihood ratio test for an appropriate Normal latent variable model for the principal component analysis. Modified EM-algorithm is used to find MLE for the model parameters. Results from simulations and real data sets give us promising evidences that the proposed method is useful in finding necessary number of components in the principal component analysis with missing values at random.

Strong Large Deviations Theorems for the Ratio of the Independent Random Variables

  • Cho, Dae-Hyeon;Jeon, Jong-Woo
    • Journal of the Korean Statistical Society
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    • 제23권2호
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    • pp.239-250
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    • 1994
  • In this paper, we prove a strong large deviations theorem for the ratio of independent randoem variables with error rate of $O(n^{-1})$. To obtain our results we use the inversion formula for the tail probability and apply the Chaganty and Sethuraman's (1985) approach.

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Optimal design of plane frame structures using artificial neural networks and ratio variables

  • Kao, Chin-Sheng;Yeh, I-Cheng
    • Structural Engineering and Mechanics
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    • 제52권4호
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    • pp.739-753
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    • 2014
  • There have been many packages that can be employed to analyze plane frames. However, because most structural analysis packages suffer from closeness of system, it is very difficult to integrate it with an optimization package. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrate Design, Analysis, Modeling, Definition, and Optimization phases into an integrative environment. The DAMDO methodology employs neural networks to integrate structural analysis package and optimization package so as not to need directly to integrate these two packages. The key problem of the DAMDO approach is how to generate a set of reasonable random designs in the first phase. According to the characteristics of optimized plane frames, we proposed the ratio variable approach to generate them. The empirical results show that the ratio variable approach can greatly improve the accuracy of the neural networks, and the plane frame optimization problems can be solved by the DAMDO methodology.