Direct Estimation Method Research Articles

Quality of life of diabetes patients in North India

Background: India is witnessing a dramatic rise in the prevalence of diabetes mellitus. In this study, quality of life (QOL) of patients with diabetes and its determinants were assessed. Second, the valuation of QOL using different methods of measurement was examined. Methods: A community-based survey comprising 306 adults diagnosed with diabetes was undertaken in an urban slum area of Chandigarh city. Direct methods of QOL assessment such as time trade-off (TTO) and Visual Analog Scale (VAS) along with indirect like EuroQol 5-Dimensional 5-Level Instrument (EQ-5D-5L) and the QOL Instrument for Indian Diabetes Patients (QOLID) were used. Multiple linear regression was used to compute coefficients to assess point estimate of QOL using the Indian QOLID tool. Results: Overall, health utility scores for a person with diabetes were 0.68 (with TTO method), 0.60–0.64 (with VAS) analog scale, and EQ-5D-5L method, respectively. Valuation of QOL using direct methods yielded utility values which were significantly higher than indirect methods (EQ-5D-5L). Conclusion: Overall, this study found that diabetes is responsible for physical, psychological, and social role disturbance among the patients. In addition, choice of using direct or indirect methods of utility estimation may have practical implications while calculating incremental cost-effectiveness ratios.

Innovative Construction of the AFPM-Type Electric Machine and the Method for Estimation of Its Performance Parameters on the Basis of the Induction Voltage Shape

The article presents an innovative construction of the Axial Flux Permanent Magnet (AFPM) machine designed for generator performance, which provides the shape of induced voltage that enables estimation of the speed and rotational angle of the machine rotor. Design solutions were proposed, the aim of which is to limit energy losses as a result of the occurrence of eddy currents. The method of direct estimation of the value of the rotational speed and rotational angle of the machine rotor was proposed and investigated on the basis of the measurements of induced voltages and machine phase currents. The advantage of the machine is the utilization of simple and easy-to-use computational procedures. The acquired results were compared with the results obtained for estimation performed by using the Unscented Kalman Filter (UKF).

Reward Value Revealed by Auction in Rhesus Monkeys.

Economic choice is thought to involve the elicitation of the subjective values of the choice options. Thus far, value estimation in animals has relied on stochastic choices between multiple options presented in repeated trials and expressed from averages of dozens of trials. However, subjective reward valuations are made moment-to-moment and do not always require alternative options; their consequences are usually felt immediately. Here, we describe a Becker-DeGroot-Marschak (BDM) auction-like mechanism that provides more direct and simple valuations with immediate consequences. The BDM encourages agents to truthfully reveal their true subjective value in individual choices ("incentive compatibility"). Male monkeys reliably placed well-ranked BDM bids for up to five juice volumes while paying from a water budget. The bids closely approximated the average subjective values estimated with conventional binary choices (BCs), thus demonstrating procedural invariance and aligning with the wealth of knowledge acquired with these less direct estimation methods. The feasibility of BDM bidding in monkeys paves the way for an analysis of subjective neuronal value signals in single trials rather than from averages; the feasibility also bridges the gap to the increasingly used BDM method in human neuroeconomics.SIGNIFICANCE STATEMENT The subjective economic value of rewards cannot be measured directly but must be inferred from observable behavior. Until now, the estimation method in animals was rather complex and required comparison between several choice options during repeated choices; thus, such methods did not respect the imminence of the outcome from individual choices. However, human economic research has developed a simple auction-like procedure that can reveal in a direct and immediate manner the true subjective value in individual choices [Becker-DeGroot-Marschak (BDM) mechanism]. The current study implemented this mechanism in rhesus monkeys and demonstrates its usefulness for eliciting meaningful value estimates of liquid rewards. The mechanism allows future neurophysiological assessment of subjective reward value signals in single trials of controlled animal tasks.

A New Method for Head Direction Estimation based on Dlib Face Detection Method and Implementation of Sine Invers Function

The detection and tracking of head movements have been such an active area of research during the past years. This area contributes highly to computer vision and has many applications of computer vision. Thus, several methods and algorithms of face detection have been proposed because they are required in most modern applications, in which they act as the cornerstone in many interactive projects. Implementation of the detected angles of the head or head direction is very useful in many fields, such as disabled people assistance, criminal behavior tracking, and other medical applications. In this paper, a new method is proposed to estimate the angles of head direction based on Dlib face detection algorithm that predicts 68 landmarks in the human face. The calculations are mainly based on the predicated landmarks to estimate three types of angles Yaw, Pitch and Roll. A python program has been designed to perform face detection and its direction. To ensure accurate estimation, the particular landmarks were selected, such that, they are not affected by the movement of the head, so, the calculated angles are approximately accurate. The experimental results showed high accuracy measures for the entire three angles according to real and predicted measures. The sample standard deviation results for each real and calculated angle were Yaw (0.0046), Pitch (0.0077), and Roll (0.0021), which confirm the accuracy of the proposed method compared with other studies. Moreover, the method performs faster which promotes accurate online tracking.

Estimating the RMSE of Small Area Estimates without the Tears

Small area estimation (SAE) methods can provide information that conventional direct survey estimation methods cannot. The use of small area estimates based on linear and generalized linear mixed models is still very limited, possibly because of the perceived complexity of estimating the root mean square errors (RMSEs) of the estimates. This paper outlines a study used to determine the conditions under which the estimated RMSEs, produced as part of statistical output (‘plug-in’ estimates of RMSEs) could be considered appropriate for a practical application of SAE methods where one of the main requirements was to use SAS software. We first show that the estimated RMSEs created using an EBLUP model in SAS and those obtained using a parametric bootstrap are similar to the published estimated RMSEs for the corn data in the seminal paper by Battese, Harter and Fuller. We then compare plug-in estimates of RMSEs from SAS procedures used to create EBLUP and EBP estimators against estimates of RMSEs obtained from a parametric bootstrap. For this comparison we created estimates of current smoking in males for 153 local government areas (LGAs) using data from the NSW Population Health Survey in Australia. Demographic variables from the survey data were included as covariates, with LGA-level population proportions, obtained mainly from the Australian Census used for prediction. For the EBLUP, the estimated plug-in estimates of RMSEs can be used, provided the sample size for the small area is more than seven. For the EBP, the plug-in estimates of RMSEs are suitable for all in-sample areas; out-of-sample areas need to use estimated RMSEs that use the parametric bootstrap.

Fast and direct optical dispersion estimation for ultrafast laser pulse compression.

In ultrashort pulse laser applications, optical dispersion seriously affects the energy concentration in the laser pulse duration and lowers the peak power. Accordingly, this study proposes a rapid dispersion estimation mechanism to facilitate the compensation of optical dispersion using a closed-loop control system. In the proposed approach, the optical dispersion information of the laser pulse is estimated directly from a frequency-resolved optical gating trace without the need for an iterative pulse-retrieval algorithm. In particular, the group delay dispersion (GDD) is determined from frequency and delay marginals, which are related to the laser spectrum and intensity autocorrelation, respectively, using a simple lookup table approach. The accuracy of the estimated GDD results is confirmed via a comparison with the spectral phase distribution of the electric field reconstructed using the principal component generalized projections algorithm. It is shown that the computation time of the proposed direct estimation method is around 13 times faster than that of the traditional iterative algorithm. It thus provides a feasible approach for enabling the real-time compensation of ultrafast laser pulse compression. Moreover, in a multiphoton-excited fluorescence imaging application, the proposed pulse compression mechanism yields an effective improvement in the intensity and contrast of the reconstructed image due to the increased nonlinear optical excitation efficiency of the optimized laser pulses.

Estimating Vertical Distribution of Leaf Water Content within Wheat Canopies after Head Emergence

Monitoring vertical profile of leaf water content (LWC) within wheat canopies after head emergence is vital significant for increasing crop yield. However, the estimation of vertical distribution of LWC from remote sensing data is still challenging due to the effects of wheat spikes and the efficacy of sensor measurement from the nadir direction. Using two-year field experiments with different growth stages after head emergence, N rates, wheat cultivars, we investigated the vertical distribution of LWC within canopies, the changes of canopy reflectance after spikes removal, the relationship between spectral indices and LWC in the upper-, middle- and bottom-layer. The interrelationship among vertical LWC were constructed, and four ratio of reflectance difference (RRD) type of indices were proposed based on the published WI and NDWSI indices to determine vertical distribution of LWC. The results indicated a bell shape distribution of LWC in wheat plants with the highest value appeared at the middle layer, and significant linear correlations between middle-LWC vs. upper-LWC and middle-LWC vs. bottom-LWC (r ≥ 0.92) were identified. The effects of wheat spikes on spectral reflectance mainly occurred in near infrared to shortwave infrared regions, which then decreased the accuracy of LWC estimation. Spectral indices at the middle layer outperformed the other two layers in LWC assessment and were less susceptible to wheat spikes effects, in particular, the newly proposed narrow-band WI-4 and NDWSI-4 indices exhibited great potential in tracking the changes of middle-LWC (R2 = 0.82 and 0.84, respectively). By taking into account the effects of wheat spikes and the interrelationship of vertical LWC within canopies, an indirect induction strategy was developed for modeling the upper-LWC and bottom-LWC. It was found that the indirect induction models based on the WI-4 and NDWSI-4 indices were more effective than the models obtained from conventional direct estimation method, with R2 of 0.78 and 0.81 for the upper-LWC estimation, and 0.75 and 0.74 for the bottom-LWC estimation, respectively.

The Epoch of Reionization 21-cm bispectrum: the impact of light-cone effects and detectability

ABSTRACT We study the spherically averaged bispectrum of the 21-cm signal from the Epoch of Reionization (EoR). This metric provides a quantitative measurement of the level of non-Gaussianity of the signal, which is expected to be high. We focus on the impact of the light-cone (LC) effect on the bispectrum and its detectability with the future SKA-Low telescope. Our investigation is based on a single reionization LC model and an ensemble of 50 realizations of the 21-cm signal to estimate the cosmic variance errors. We calculate the bispectrum with a new, optimized direct estimation method, DviSukta, which calculates the bispectrum for all possible unique triangles. We find that the LC effect becomes important on scales $k_1 \lesssim 0.1\, {\rm Mpc}^{-1}$, where, for most triangle shapes, the cosmic variance errors dominate. Only for the squeezed limit triangles, the impact of the LC effect exceeds the cosmic variance. Combining the effects of system noise and cosmic variance we find that ∼3σ detection of the bispectrum is possible for all unique triangle shapes around a scale of $k_1 \sim 0.2\, {\rm Mpc}^{-1}$, and cosmic variance errors dominate above and noise errors below this length-scale. Only the squeezed limit triangles are able to achieve a more than 5σ significance over a wide range of scales, $k_1\lesssim 0.8\, {\rm Mpc}^{-1}$. Our results suggest that among all the possible triangle combinations for the bispectrum, the squeezed limit one will be the most measurable and hence useful.

Modeling, state of charge estimation, and charging of lithium‐ion battery in electric vehicle: A review

Extension of driving range and battery run time optimization are necessary key points in the modeling of Electric Vehicle (EV). In this view, Battery Management System (BMS) plays a major role to ensure a safe and trustworthy battery operation, especially when using Lithium-ion (Li-ion) batteries in an electric vehicle. Key function of BMS is State of Charge (SoC) estimation. A well-parameterized battery model is required for accurate state estimation. Consequently, the major factors to be considered in battery modeling are the SoC estimation and charging methodology of an effective BMS development. By focusing on these features, in this paper, the well-known battery models such as the electrochemical model, equivalent circuit model, and data-driven model are comprehensively reviewed along with their strengths and weaknesses. Further, the SoC estimation of a battery is also discussed by using standard methodologies such as direct estimation methods and model-based estimation methods. The comparisons of the three most distinct battery models and the classification of SoC estimation techniques to develop a proper BMS for EV with the focus on accuracy, configuration effort, computational complexity, ease of implementation, and real-time applications are systematically reviewed. In addition to this, convenient battery charging approaches with the consideration of some constraints such as charging time, charging efficiency, state of charge, state of health, charging voltage threshold, capacity fade, power fade, aging effect, capacity utilization, impedance rise, and temperature rise of the battery in EV are presented. Finally, the perspectives of the existing work and the recommended future research work of BMS are summarized.

Dynamic changes in moisture content and applicability analysis of a typical litter prediction model in Yunnan Province.

BackgroundForest fire risk predictions are based on the most conservation daily predictions, and the lowest litter moisture content of each day is often used to predict the day’s fire risk. Yunnan Province is the area with the most frequent and serious forest fires in China, but there is almost no research on the dynamic changes and model predictions of the litter moisture content in this area. Therefore, to reduce the occurrence of forest fires and improve the accuracy of forest fire risk predictions, it is necessary to understand these dynamic changes and establish an appropriate prediction model for the typical litter moisture content in Yunnan Province.MethodDuring the fire prevention period, daily dynamic changes in the litter moisture content are obtained by monitoring the daily step size, and the relationships between the litter moisture content and meteorological elements are analyzed. In this study, the meteorological element regression method, moisture code method and direction estimation method are selected to establish litter moisture content prediction models, and the applicability of each model is analyzed.ResultsWe found that dynamic changes in the litter moisture content have obvious lags compared with meteorological elements, and the litter moisture content is mainly related to the air temperature, relative humidity and wind speed. With an increase in the sampling interval of meteorological elements, the significances of these correlations first increase and then decrease. The moisture content value obtained by directly using the moisture code method in the Fire Weather Index (FWI) significantly different from the measured value, so this method is not applicable. The mean absolute error (MAE) and mean relative error (MRE) values obtained with the meteorological element regression method are 2.97% and 14.06%, those from the moisture code method are 3.27% and 14.07%, and those from the direct estimation method are 2.82% and 12.76%, respectively.ConclusionsThe direct estimation method has the lowest error and the strongest extrapolation ability; this method can meet the needs of daily fire forecasting. Therefore, it is feasible to use the direct estimation method to predict litter moisture contents in Yunnan Province.

Simple and direct estimation method for split-off hole effective mass from Franz–Keldysh oscillations appearing in photoreflectance spectra: a feasibility study using GaAs epitaxial layer structures at room temperature

We investigated the feasibility of directly estimating split-off hole effective mass m so from Franz–Keldysh oscillations using non-destructive and non-invasive photoreflectance spectroscopy. We used an undoped/n-type GaAs epitaxial structure and two GaAs p–i–n diode structures. We observed the phenomenon that Franz–Keldysh oscillations, which originate both the E 0 fundamental transition and from the E 0 + Δso transition energy, appear in the photoreflectance spectra at room temperature. Initially, from the electro-optic constant ℏΘ HH of the Franz–Keldysh oscillations originating from the E 0 fundamental transition, we deduced the built-in electric field F in each sample with the use of the relation ℏΘ HH = (e 2ℏ2 F 2/2μ HH)1/3, where the quantity μ HH is the reduced effective mass of the electron and heavy hole. In the next step, we calculated the reduced effective mass μ so of the electron and split-off hole using the relation ℏΘ so = (e 2ℏ2 F 2/2μ so)1/3, where the quantity ℏΘ so is the electro-optic constant of the Franz–Kelysh oscilations from the E 0 + Δso transition. Finally, we estimated the split-off hole effective mass m so from the reduced effective mass μ so. The estimated split-off hole effective mass agrees with the reported value obtained experimentally. Thus, we conclude that the split-off hole effective mass is estimatable from analyzing the Franz–Keldysh oscillations in the photoreflectance spectra. We also compare the present hole effective masses to those theoretically known and discuss the appropriateness of the electronic-band calculations.

Underwater mobile gravity measurement data processing using continuous-discrete Kalman filter

To solve the data fusion problem in underwater mobile gravity measurement, a direct estimation method based on pose information is proposed. First, the state model is established using the continuous evolution equation of the state. Then, to obtain the space model of the state for data fusion of the measured underwater mobile gravity, the measurement model is constructed according to the external measurement equation. To solve the continuous-discrete space model of the state, the numerical integration method for continuous time updates and the virtual sampling iterative method for discrete observation updates are proposed, which can be used for the time update case and the observation update case, respectively. In this way, the continuous-discrete iterative extended Kalman filter for direct pose estimation is formed. The proposed methods are compared and analyzed based on the motion simulation data of different carrier and inertial measurement unit simulation data for different accuracy levels. The method proposed in this paper has been validated by carrying out the experiments on a lake. The results show that the method proposed in this paper can minimize the effect of accuracy of initial alignment on strapdown gravimetric measurement and shows a better dynamic estimation performance.

Non-parametric estimation of a Langevin model driven by correlated noise

Langevin models are frequently used to model various stochastic processes in different fields of natural and social sciences. They are adapted to measured data by estimation techniques such as maximum likelihood estimation, Markov chain Monte Carlo methods, or the non-parametric direct estimation method introduced by Friedrich et al. The latter has the distinction of being very effective in the context of large data sets. Due to their $\delta$-correlated noise, standard Langevin models are limited to Markovian dynamics. A non-Markovian Langevin model can be formulated by introducing a hidden component that realizes correlated noise. For the estimation of such a partially observed diffusion a different version of the direct estimation method was introduced by Lehle et al. However, this procedure includes the limitation that the correlation length of the noise component is small compared to that of the measured component. In this work we propose another version of the direct estimation method that does not include this restriction. Via this method it is possible to deal with large data sets of a wider range of examples in an effective way. We discuss the abilities of the proposed procedure using several synthetic examples.

SMALL AREA ESTIMATION METHOD WITH EMPIRICAL BAYES BASED ON BETA BINOMIAL MODEL IN GENERATED DATA

Small Area Estimation is one of the methods that can be used to estimate parameters in an area that has a small population. This study aims to estimate the value of the binary data parameter using the direct estimation method and an indirect estimation method by using the Empirical Bayes approach. To illustrate the method, we consider three conditions: direct estimator, empirical Bayes (EB) with auxiliary variables, and empirical Bayes without auxiliary variables. The smaller value of Mean Square Error is used to determine the better method. The results showed that the indirect estimation methods (EB method) gave the parameter value that was not much different from the direct estimation value. Then, the MSE values of indirect estimation with an auxiliary variable are smaller than the direct estimation method.

Remote Sensing of Ecosystem Water Use Efficiency: A Review of Direct and Indirect Estimation Methods

Water use efficiency (WUE) is a key index for understanding the ecosystem of carbon–water coupling. The undistinguishable carbon–water coupling mechanism and uncertainties of indirect methods by remote sensing products and process models render challenges for WUE remote sensing. In this paper, current progress in direct and indirect methods of WUE estimation by remote sensing is reviewed. Indirect methods based on gross primary production (GPP)/evapotranspiration (ET) from ground observation, processed models and remote sensing are the main ways to estimate WUE in which carbon and water cycles are independent processes. Various empirical models based on meteorological variables and remote sensed vegetation indices to estimate WUE proved the ability of remotely sensed data for WUE estimating. The analytical model provides a mechanistic opportunity for WUE estimation on an ecosystem scale, while the hypothesis has yet to be validated and applied for the shorter time scales. An optimized response of canopy conductance to atmospheric vapor pressure deficit (VPD) in an analytical model inverted from the conductance model has been also challenged. Partitioning transpiration (T) and evaporation (E) is a more complex phenomenon than that stated in the analytic model and needs a more precise remote sensing retrieval algorithm as well as ground validation, which is an opportunity for remote sensing to extrapolate WUE estimation from sites to a regional scale. Although studies on controlling the mechanism of environmental factors have provided an opportunity to improve WUE remote sensing, the mismatch in the spatial and temporal resolution of meteorological products and remote sensing data, as well as the uncertainty of meteorological reanalysis data, add further challenges. Therefore, improving the remote sensing-based methods of GPP and ET, developing high-quality meteorological forcing datasets and building mechanistic remote sensing models directly acting on carbon–water cycle coupling are possible ways to improve WUE remote sensing. Improvement in direct WUE remote sensing methods or remote sensing-driven ecosystem analysis methods can promote a better understanding of the global ecosystem carbon–water coupling mechanisms and vegetation functions–climate feedbacks to serve for the future global carbon neutrality.

RF-Based Indoor Moving Direction Estimation Using a Single Access Point

Indoor moving direction and rotation angle measurements are crucial to many ubiquitous mobile computing applications. Most of the state-of-the-art approaches rely on inertial sensors, e.g., accelerometers, gyroscopes, and magnetometers, which suffer from severe accumulative errors or accuracy degradation indoors. This article presents an RF-based direction estimation method, which utilizes the off-the-shelf commodity WiFi devices for accurate moving direction and in-place rotation angle estimation. The proposed approach employs a novel 2-D antenna array and leverages the spatial decay property of the time-reversal resonating strength. First, the moving speeds along different directions, specified by the 2-D array, are derived using virtual antenna alignment. The precise estimation of the device’s moving direction is then achieved by combining the obtained velocity information and the a prior knowledge of the array’s geometry layout. Experiments in a multipath-rich indoor environment have shown that the median error for moving direction estimation is 6.9°, which outperforms the accelerometer counterpart. The results also verify the good accuracy of in-place rotation angle estimation without any accumulative error, which beats the gyroscope in long-term tests. Because the proposed approach can achieve high accuracy without accumulative drifts, it is a promising candidate solution to applications that require accurate direction information.

Which LDL Value Should Clinicians Look at?

Objectives LDL cholesterol is routinely estimated by the Friedewald formula to guide the treatment of dyslipidemia. However, Friedewald equation has certain limitations, especially with high triglyceride levels. Direct methods are available for LDL estimation but have received relatively little scrutiny in the Indian setting. This study was aimed at comparing the calculative and direct methods of LDL estimation in Indian hyperlipidemic patients. Materials and Methods In this observational study, data from 380 consecutive lipid profiles of patients visiting a tertiary care hospital in Mumbai were analyzed retrospectively. CHOD PAP method was used to estimate total cholesterol. Enzymatic colorimetric method was used to estimate triglycerides. Enzyme selective protection method was used to estimate HDL. Direct LDL was estimated by homogenous enzymatic colorimetric assay and very low-density lipoprotein was calculated, whereas Friedewald’s formula was used to derive calculated LDL. Results Total cholesterol values correlated positively with the LDL values measured by both methods. However, a statistically significant difference was noted between the correlation coefficients of both the methods. Triglyceride values correlated weakly with the LDL levels measured by both the methods. A weak negative correlation was observed with LDL by the calculated method, whereas a weak positive correlation existed between TG and LDL by the direct method. The difference between the correlation coefficients was statistically significant. Conclusion Both direct and calculated methods of LDL estimation have their limitations. A robust study with a larger sample size is needed to further investigate whether the differences in the different LDL estimation methods can translate to “clinical relevance” in the Indian setting.

Evaluating the Approaches of Small Area Estimation Using Poverty Mapping Data

Nowadays, estimation demand in statistics is increased worldwide to seek out an estimate, or approximation, which may be a value which will be used for various purpose, albeit the input data could also be incomplete, uncertain, or unstable. The development of different estimation methods is trying to provide most accurate estimate and estimation theory deals with finding estimates with good properties. The demand of small area estimation (SAE) method has been increasing rapidly around the world because of its reliability compared to the traditional direct estimation methods, especially in the case of small sample size. This paper mainly focuses on the comparison of several indirect small area estimation methods (poststratified synthetic, SSD and EB estimates) with traditional direct estimator based on a renowned data set. Direct estimator is approximately unbiased but SSD and Post-stratified synthetic estimator is extreme biased. To cope up the problem, we conduct another model-based estimation procedure namely Empirical Bayes (EB) estimator, which is unbiased and compare them using their coefficient of variation (CV). To check the model assumption, we used Q-Q plot as well as a Histogram to confirm the normality, bivariate correlation, Akaike information criterion (AIC). JEL classification numbers: C13, C51, C51. Keywords: Small Area Estimation, Direct Estimation, Indirect Estimation, Empirical Bayes Estimator, Poverty Mapping.

A Direct Method for the Simultaneous Estimation of Self-Steepening and the Fractional Raman Contribution in Fiber Optics

We propose an original, simple, and direct method for the simultaneous estimation of the self-steepening parameter and the fractional Raman contribution in fiber optics. Our proposal is based on the dependence of the modulation instability gain on both parameters, as obtained from a linear stability analysis of the newly introduced photon-conserving generalized nonlinear Schrödinger equation (pcGNLSE), and requires only the CW or quasi-CW pumping of the waveguide under test and a few direct spectral measurements. Further, we demonstrate the feasibility of the estimation procedure by means of detailed simulations for typical waveguide parameters in relevant spectral ranges. Last, we discuss the range of applicability of the proposed method and compare its results, advantages, and disadvantages with a recently introduced method based on short-pulse dynamics.

A Bayesian Logit-Normal Model in Small Area Estimation

The Logit-Normal model is one of the GLM Bayes models with random covariates used in binary data. This study aimed to examine and evaluate the characteristics of the Logit-Normal model. The second objective was to apply the Logit-Normal model to estimate the proportion of poverty in the small area of Mukomuko District in Bengkulu Province. We used the Hierarchical Bayes (HB) method to estimate parameters model. The simulation results obtained from the optimum number of iterations and gibbs samples, namely 500 iterations and 100 gibbs samples, respectively. In addition, when seen the value of has the same tendency with the parameter pi and . The value of tends to overestimate at ⩽ 60%. Conversely, tends to underestimate > 60%. Furthermore, in the simulation results the estimated value of variance and MSE tends to be smaller than the variance of proportion. The application of the HB method for Logit-Normal model in the Mukomuko District poverty data produces which has the same tendency as the result of direct estimator (). The majority (21 villages) value of var() are smaller or equal to the var(). This indicates that the estimation using the HB method can improve the estimation of the proportion parameters obtained by using the direct estimation method on poverty data.