• Communications for Statistical Applications and Methods
• /
• v.12 no.2
• /
• pp.285-294
• /
• 2005

This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. Method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, three dimensional nonlinear equations are simplified to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, L-ME (or MME) is recommended to use for small sample size( n$\le$100) while MLE is good for large sample size.

• 한국데이터정보과학회:학술대회논문집
• /
• 2006.04a
• /
• pp.163-169
• /
• 2006

This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. The method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, ike dimensional nonlinear equations are simplied to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, the L-ME is recommended to use for small sample size $(n\leq100)$ while MLE is good for large sample size.

• Journal of the Korean Statistical Society
• /
• v.27 no.4
• /
• pp.507-514
• /
• 1998

The minimum distance estimation based on the L$_2$ distance between a model density and a density estimator is studied from M-estimation point of view. We will show that how a model density and a density estimator are incorporated in order to create an M-estimation function. This method enables us to create an M-estimating function reflecting the natures of both an assumed model density and a given set of data. Some new types of M-estimation functions for estimating a location and scale parameters are introduced.

• Communications for Statistical Applications and Methods
• /
• v.27 no.4
• /
• pp.469-486
• /
• 2020

Entropy is an important term in statistical mechanics that was originally defined in the second law of thermodynamics. In this paper, we consider the maximum likelihood estimation (MLE), maximum product spacings estimation (MPSE) and Bayesian estimation of the entropy of an inverse Weibull distribution (InW) under a generalized type I progressive hybrid censoring scheme (GePH). The MLE and MPSE of the entropy cannot be obtained in closed form; therefore, we propose using the Newton-Raphson algorithm to solve it. Further, the Bayesian estimators for the entropy of InW based on squared error loss function (SqL), precautionary loss function (PrL), general entropy loss function (GeL) and linex loss function (LiL) are derived. In addition, we derive the Lindley's approximate method (LiA) of the Bayesian estimates. Monte Carlo simulations are conducted to compare the results among MLE, MPSE, and Bayesian estimators. A real data set based on the GePH is also analyzed for illustrative purposes.

• Journal of Oral Medicine and Pain
• /
• v.14 no.1
• /
• pp.43-55
• /
• 1989

The need of age estimation for identification was increased by complexity of society, and the tooth was used widely for age estimation because of less individual deviation than the other organ. The age estimation using the tooth had several methods. Recently, the one using the racemization of aminoacid in the tooth was admitted more accurate than the other methods, especially in old age. But, this study was not tried in our country, and I would report the result of experiment about age estimation using racemization of dentine. I selected 40-Whole dentine sample from extracted teeth, those were reserved in natural dried condition for 2 weeks~ 1year and calculated the estimation of age from the ratio of D-aminoacid and L-aminoacid (D/L ratio) using gaschromatography and the results were below. 1. The aminoacids showed apparent K/L ratio in dentine were aspartic acid, serine. 2. The aspartic acid showed the highest racemic rate and its rate was 0.0012$\pm$0.0003/yr. 3. The relation between the actual age and K/L ratio was very positive correlation(r+0.954) in the estimation of age using aspartic acid. 4. The deviation between the estimated age using D/L ratio of aspartic acid and actual age was $\pm$3.32.

• The Korean Journal of Applied Statistics
• /
• v.18 no.1
• /
• pp.43-56
• /
• 2005

In this study, a robust estimation method for the first-order autocorrelation coefficient in the time series model following AR(l) process with additive outlier(AO) is investigated. We propose the L-type trimmed least squares estimation method using the preliminary estimator (PE) suggested by Rupport and Carroll (1980) in multiple regression model. In addition, using Mallows' weight function in order to down-weight the outlier of X-axis, the bounded-influence PE (BIPE) estimator is obtained and the mean squared error (MSE) performance of various estimators for autocorrelation coefficient are compared using Monte Carlo experiments. From the results of Monte-Carlo study, the efficiency of BIPE(LAD) estimator using the generalized-LAD to preliminary estimator performs well relative to other estimators.

• East Asian mathematical journal
• /
• v.14 no.2
• /
• pp.421-427
• /
• 1998

In this paper we provide sufficient conditions which ensure the strong consistency of $L_p$-norm estimation in nonlinear regression model when the probability distribution of the errors term is symmetric about zero. The least absolute deviation and least square estimation are discussed as special cases of the proposed estimation.

• Journal of the Korean Statistical Society
• /
• v.27 no.2
• /
• pp.153-163
• /
• 1998

We investigate density estimation problem in the L$^{\infty}$ norm and show that the iii optimal minimax rates are achieved for smooth classes of weakly dependent stationary sequences. Our results are then applied to give uniform convergence rates for various problems including the Gibbs sampler.

• The KIPS Transactions:PartB
• /
• v.14B no.4
• /
• pp.241-248
• /
• 2007

An L-curve corner detection method is proposed for the determination of the regularization parameter in optical flow estimation. The method locates the positive peak whose curvature difference from the just right-hand negative valley is the maximum in the curvature plot of the L-curve. while the existing curvature-method simply finds the maximum in the plot. Experimental results show that RMSE of the estimated optical flow is greater only by 0.02 pixels-per-frame than the least in the average sense. The proposed method is also compared with an existing curvature-method and the adaptive pruning method, resulting in the optical flow estimation closest to the least RMSE.

• Journal of the Korean Statistical Society
• /
• v.16 no.2
• /
• pp.80-91
• /
• 1987

Minimum $L_i$ norm estimation is a robust procedure ins the sense that it leads to an estimator which has greater statistical eficiency than the least squares estimator in the presence of outliers. And the $L_1$ norm estimator has some desirable statistical properties. In this paper a new computational procedure for $L_1$ norm estimation is proposed which combines the idea of reweighted least squares method and the linear programming approach. A modification of the projective transformation method is employed to solve the linear programming problem instead of the simplex method. It is proved that the proposed algorithm terminates in a finite number of iterations.