• Title/Summary/Keyword: Estimators

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Ratio-Cum-Product Estimators of Population Mean Using Known Population Parameters of Auxiliary Variates

  • Tailor, Rajesh;Parmar, Rajesh;Kim, Jong-Min;Tailor, Ritesh
    • Communications for Statistical Applications and Methods
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    • v.18 no.2
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    • pp.155-164
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    • 2011
  • This paper suggests two ratio-cum-product estimators of finite population mean using known coefficient of variation and co-efficient of kurtosis of auxiliary characters. The bias and mean squared error of the proposed estimators with large sample approximation are derived. It has been shown that the estimators suggested by Upadhyaya and Singh (1999) are particular case of the suggested estimators. Almost ratio-cum product estimators of suggested estimators have also been obtained using Jackknife technique given by Quenouille (1956). An empirical study is also carried out to demonstrate the performance of the suggested estimators.

Estimation for Mean and Standard Deviation of Normal Distribution under Type II Censoring

  • Kim, Namhyun
    • Communications for Statistical Applications and Methods
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    • v.21 no.6
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    • pp.529-538
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    • 2014
  • In this paper, we consider maximum likelihood estimators of normal distribution based on type II censoring. Gupta (1952) and Cohen (1959, 1961) required a table for an auxiliary function to compute since they did not have an explicit form; however, we derive an explicit form for the estimators using a method to approximate the likelihood function. The derived estimators are a special case of Balakrishnan et al. (2003). We compare the estimators with the Gupta's linear estimators through simulation. Gupta's linear estimators are unbiased and easily calculated; subsequently, the proposed estimators have better performance for mean squared errors and variances, although they show bigger biases especially when the ratio of the complete data is small.

Generalized Higher Order Energy Based Instantaneous Amplitude and Frequency Estimation and Their Applications to Power Disturbance Detection

  • Iem, Byeong-Gwan
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.2
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    • pp.162-166
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    • 2012
  • The instantaneous amplitude (IA) based on the higher order differential energy operator is proposed. And its general form for arbitrary order is also proposed. The various definitions of the IA and the instantaneous frequency (IF) estimators are considered. The IA and IF estimators based on the energy operators need less computational cost than the conventional IF and IA estimators exploiting the Hilbert transform. The IF and IA estimators are compared in terms of the frequency and amplitude tracking accuracy of the AM-FM signals. For noiseless case, the IA and IF estimators based on the Teager-Kaiser energy operator show better tracking performance than the IF and IA estimators based on the higher energy operators. However, under noisy condition, the IF and IA estimator based on the higher order energy operators with the order 3 and 4 show better tracking than the Teager-Kaiser energy based estimators. The IF and IA estimators are applied to signals in the various power anomalies to show their usefulness as the disturbance detectors.

CONFLICT AMONG THE SHRINKAGE ESTIMATORS INDUCED BY W, LR AND LM TESTS UNDER A STUDENT'S t REGRESSION MODEL

  • Kibria, B.M.-Golam
    • Journal of the Korean Statistical Society
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    • v.33 no.4
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    • pp.411-433
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    • 2004
  • The shrinkage preliminary test ridge regression estimators (SPTRRE) based on Wald (W), Likelihood Ratio (LR) and Lagrangian Multiplier (LM) tests for estimating the regression parameters of the multiple linear regression model with multivariate Student's t error distribution are considered in this paper. The quadratic biases and risks of the proposed estimators are compared under both null and alternative hypotheses. It is observed that there is conflict among the three estimators with respect to their risks because of certain inequalities that exist among the test statistics. In the neighborhood of the restriction, the SPTRRE based on LM test has the smallest risk followed by the estimators based on LR and W tests. However, the SPTRRE based on W test performs the best followed by the LR and LM based estimators when the parameters move away from the subspace of the restrictions. Some tables for the maximum and minimum guaranteed efficiency of the proposed estimators have been given, which allow us to determine the optimum level of significance corresponding to the optimum estimator among proposed estimators. It is evident that in the choice of the smallest significance level to yield the best estimator the SPTRRE based on Wald test dominates the other two estimators.

Some efficient ratio-type exponential estimators using the Robust regression's Huber M-estimation function

  • Vinay Kumar Yadav;Shakti Prasad
    • Communications for Statistical Applications and Methods
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    • v.31 no.3
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    • pp.291-308
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    • 2024
  • The current article discusses ratio type exponential estimators for estimating the mean of a finite population in sample surveys. The estimators uses robust regression's Huber M-estimation function, and their bias as well as mean squared error expressions are derived. It was campared with Kadilar, Candan, and Cingi (Hacet J Math Stat, 36, 181-188, 2007) estimators. The circumstances under which the suggested estimators perform better than competing estimators are discussed. Five different population datasets with a well recognized outlier have been widely used in numerical and simulation-based research. These thorough studies seek to provide strong proof to back up our claims by carefully assessing and validating the theoretical results reported in our study. The estimators that have been proposed are intended to significantly improve both the efficiency and accuracy of estimating the mean of a finite population. As a result, the results that are obtained from statistical analyses will be more reliable and precise.

A Note on Adaptive Estimation for Nonlinear Time Series Models

  • Kim, Sahmyeong
    • Journal of the Korean Statistical Society
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    • v.30 no.3
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    • pp.387-406
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    • 2001
  • Adaptive estimators for a class of nonlinear time series models has been proposed by several authors. Koul and Schick(1997) proposed the adaptive estimators without sample splitting for location-type time series models. They also showed by simulation that the adaptive estimators without sample splitting have smaller mean squared errors than those of the adaptive estimators with sample splitting. the present paper generalized the result in a case of location-scale type nonlinear time series models by simulation.

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Test of the Hypothesis based on Nonlinear Regression Quantiles Estimators

  • Choi, Seung-Hoe
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.153-165
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    • 2003
  • This paper considers the likelihood ratio test statistic based on nonlinear regression quantiles estimators in order to test of hypothesis about the regression parameter $\theta_o$ and derives asymptotic distribution of proposed test statistic under the null hypothesis and a sequence of local alternative hypothesis. The paper also investigates asymptotic relative efficiency of the proposed test to the test based on the least squares estimators or the least absolute deviation estimators and gives some examples to illustrate the application of the main result.

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Estimation for the Half-Triangle Distribution Based on Progressively Type-II Censored Samples

  • Han, Jun-Tae;Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.3
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    • pp.951-957
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    • 2008
  • We derive some approximate maximum likelihood estimators(AMLEs) and maximum likelihood estimator(MLE) of the scale parameter in the half-triangle distribution based on progressively Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples. We also obtain the approximate maximum likelihood estimators of the reliability function using the proposed estimators. We compare the proposed estimators in the sense of the mean squared error.

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Some Alternative Classes of Shrinkage Estimators for a Scale Parameter of the Exponential Distribution

  • Singh, Housila P.;Singh, Sarjinder;Kim, Jong-Min
    • The Korean Journal of Applied Statistics
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    • v.25 no.2
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    • pp.301-309
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    • 2012
  • This paper proposes some alternative classes of shrinkage estimators and analyzes their properties. In particular, some new shrinkage estimators are identified and compared with Pandey (1983), Pandey and Srivastav (1985) and Jani (1991) estimators. Numerical illustrations are also provided.

Bootstrap Confidence Intervals of Ridge Estimators in Mixture Experiments (혼합물실험에서 능형추정량에 대한 붓스트랩 신뢰구간)

  • Jang, Dae-Heung
    • Journal of Korean Society for Quality Management
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    • v.34 no.3
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    • pp.62-65
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    • 2006
  • We can use the ridge regression as a means for stabilizing the coefficient estimators in the fitted model when performing experiments in highly constrained regions causes collinearity problems in mixture experiments. But there is no theory available on which to base statistical inference of ridge estimators. The bootstrap could be used to seek the confidence intervals of ridge estimators.