• Title/Summary/Keyword: least-squares estimation

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What Prompted Shadow Banking in China? Wealth Management Products and Regulatory Arbitrage

  • SHAH, Syed Mehmood Raza;LI, Jianjun;FU, Qiang
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.12
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    • pp.63-72
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    • 2020
  • Shadow banking in China has been growing rapidly; banks use wealth management products aggressively to evade regulatory constraints. The loan-to-deposit ratio or LDR targets both sides of the balance sheet; loans in terms of asset-side, and deposits in terms of liabilities-side; banks needed to control and maintain both sides. Regulators restricted Chinese banks to maintain a 75% limit for their loan-depositratio. Banks' needed to either lower their loans or increase the deposits; WMPs helped banks to evade this limit. Banks issue more WMPs to control and manage a 75% statutory ceiling LDR. This WMPs-LDR positive association disappeared post-2015 period. This study empirically examined how Chinese banks use WMPs issuance to avoid regulatory constraints. Quarterly panel data for 30 top Chinese banks were used by analyzing pre-2015 (during the 75% LDR limit) and post-2015 (after removal of the LDR limit). This study also performed fixed-effects model as recommended by the Hausman specification test, with feasible generalized least squares FGLS estimation technique. The results of this study show that for the pre-2015 period, Chinese banks use issuance of WMPs aggressively to manage their LDR limit; this WMPs-LDR relationship disappeared post-2015 period. Moreover, SMBs use WMPs more eagerly as compare to Big4 banks.

Precise Orbit Determination Based on the Unscented Transform for Optical Observations

  • Hwang, Hyewon;Lee, Eunji;Park, Sang-Young
    • Journal of Astronomy and Space Sciences
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    • v.36 no.4
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    • pp.249-264
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    • 2019
  • In this study, the precise orbit determination (POD) software is developed for optical observation. To improve the performance of the estimation algorithm, a nonlinear batch filter, based on the unscented transform (UT) that overcomes the disadvantages of the least-squares (LS) batch filter, is utilized. The LS and UT batch filter algorithms are verified through numerical simulation analysis using artificial optical measurements. We use the real optical observation data of a low Earth orbit (LEO) satellite, Cryosat-2, observed from optical wide-field patrol network (OWL-Net), to verify the performance of the POD software developed. The effects of light travel time, annual aberration, and diurnal aberration are considered as error models to correct OWL-Net data. As a result of POD, measurement residual and estimated state vector of the LS batch filter converge to the local minimum when the initial orbit error is large or the initial covariance matrix is smaller than the initial error level. However, UT batch filter converges to the global minimum, irrespective of the initial orbit error and the initial covariance matrix.

Probabilistic damage detection of structures with uncertainties under unknown excitations based on Parametric Kalman filter with unknown Input

  • Liu, Lijun;Su, Han;Lei, Ying
    • Structural Engineering and Mechanics
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    • v.63 no.6
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    • pp.779-788
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    • 2017
  • System identification and damage detection for structural health monitoring have received considerable attention. Various time domain analysis methodologies based on measured vibration data of structures have been proposed. Among them, recursive least-squares estimation of structural parameters which is also known as parametric Kalman filter (PKF) approach has been studied. However, the conventional PKF requires that all the external excitations (inputs) be available. On the other hand, structural uncertainties are inevitable for civil infrastructures, it is necessary to develop approaches for probabilistic damage detection of structures. In this paper, a parametric Kalman filter with unknown inputs (PKF-UI) is proposed for the simultaneous identification of structural parameters and the unmeasured external inputs. Analytical recursive formulations of the proposed PKF-UI are derived based on the conventional PKF. Two scenarios of linear observation equations and nonlinear observation equations are discussed, respectively. Such a straightforward derivation of PKF-UI is not available in the literature. Then, the proposed PKF-UI is utilized for probabilistic damage detection of structures by considering the uncertainties of structural parameters. Structural damage index and the damage probability are derived from the statistical values of the identified structural parameters of intact and damaged structure. Some numerical examples are used to validate the proposed method.

A Study on the Uncertainty Estimation of Flowmeter Calibrator with Two Master Flowmeters (2개의 기준유량계를 이용한 유량계 교정장치의 측정불확도 평가에 관한 연구)

  • Choi Jong Oh;Lee Woan Kyu;Lim Ki Won
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.28 no.10
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    • pp.1219-1230
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    • 2004
  • Comparing to the gravimetric and volumetric method, the flowmeter calibration based on the master meter method is relatively economical and convenient, especially for high flowrate. The uncertainty of flow quantity and flowrate using the master meter method was evaluated according to the GUM (Guide to the Expression of Uncertainty in Measurement). In order to apply for the wider flow range, two master meters (electromagnetic flow meter) were employed as reference flowmeters. The uncertainty of the master meter was obtained by combining the statistical variation of the repeated measurements and the variation of fluid density and pipe material due to temperature and pressure changes were scrutinized. for a practical application, the uncertainty of calibrator, whose measuring capacity of 1000 ㎥/h obtained by employing two 500 ㎥/h electromagnetic How meters, was evaluated. The uncertainty budget shows the quantitative contribution of each uncertainty component to the overall uncertainty of the calibrator. As a result, it was found that the dominant uncertainties were from the master meter, which was evaluated statistically, and from the process of least squares fitting. On the contrary, the uncertainties arising from the variation of the fluid density and the pipe volume due to the temperature and pressure were negligible.

Quantile regression using asymmetric Laplace distribution (비대칭 라플라스 분포를 이용한 분위수 회귀)

  • Park, Hye-Jung
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.6
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    • pp.1093-1101
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    • 2009
  • Quantile regression has become a more widely used technique to describe the distribution of a response variable given a set of explanatory variables. This paper proposes a novel modelfor quantile regression using doubly penalized kernel machine with support vector machine iteratively reweighted least squares (SVM-IRWLS). To make inference about the shape of a population distribution, the widely popularregression, would be inadequate, if the distribution is not approximately Gaussian. We present a likelihood-based approach to the estimation of the regression quantiles that uses the asymmetric Laplace density.

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A Fast and Precise Blind I/Q Mismatch Compensation for Image Rejection in Direct-Conversion Receiver

  • Kim, Suna;Yoon, Dae-Young;Park, Hyung Chul;Yoon, Giwan;Lee, Sang-Gug
    • ETRI Journal
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    • v.36 no.1
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    • pp.12-21
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    • 2014
  • In this paper, we propose a new digital blind in-phase/quadrature-phase (I/Q) mismatch compensation technique for image rejection in a direct-conversion receiver (DCR). The proposed image-rejection circuit adopts DC offset cancellation and a sign-sign least mean squares (LMS) algorithm with a unique step size adaptation both for a fast and precise I/Q mismatch estimation. In addition, several performance-optimizing design considerations related to accuracy, speed, and hardware simplicity are discussed. The implementation of the proposed circuit in an FPGA results in an image-rejection ratio (IRR) of 65 dB, which is the best performance with modulated signals, along with an adaptation time of 0.9 seconds, which is a tenfold increase in the compensation speed as compared to previously reported circuits. The proposed technique will be a promising solution in the area of image rejection to increase both the speed and accuracy of future DCRs.

Predicting Soil Chemical Properties with Regression Rules from Visible-near Infrared Reflectance Spectroscopy

  • Hong, Suk Young;Lee, Kyungdo;Minasny, Budiman;Kim, Yihyun;Hyun, Byung Keun
    • Korean Journal of Soil Science and Fertilizer
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    • v.47 no.5
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    • pp.319-323
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    • 2014
  • This study investigates the prediction of soil chemical properties (organic matter (OM), pH, Ca, Mg, K, Na, total acidity, cation exchange capacity (CEC)) on 688 Korean soil samples using the visible-near infrared reflectance (VIS-NIR) spectroscopy. Reflectance from the visible to near-infrared spectrum (350 to 2500 nm) was acquired using the ASD Field Spec Pro. A total of 688 soil samples from 168 soil profiles were collected from 2009 to 2011. The spectra were resampled to 10 nm spacing and converted to the 1st derivative of absorbance (log (1/R)), which was used for predicting soil chemical properties. Principal components analysis (PCA), partial least squares regression (PLSR) and regression rules model (Cubist) were applied to predict soil chemical properties. The regression rules model (Cubist) showed the best results among these, with lower error on the calibration data. For quantitatively determining OM, total acidity, CEC, a VIS-NIR spectroscopy could be used as a routine method if the estimation quality is more improved.

Torusity Tolerance Verification using Swarm Intelligence

  • Prakasvudhisarn, Chakguy;Kunnapapdeelert, Siwaporn
    • Industrial Engineering and Management Systems
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    • v.6 no.2
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    • pp.94-105
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    • 2007
  • Measurement technology plays an important role in discrete manufacturing industry. Probe-type coordinate measuring machines (CMMs) are normally used to capture the geometry of part features. The measured points are then fit to verify a specified geometry by using the least squares method (LSQ). However, it occasionally overestimates the tolerance zone, which leads to the rejection of some good parts. To overcome this drawback, minimum zone approaches defined by the ANSI Y14.5M-1994 standard have been extensively pursued for zone fitting in coordinate form literature for such basic features as plane, circle, cylinder and sphere. Meanwhile, complex features such as torus have been left to be dealt-with by the use of profile tolerance definition. This may be impractical when accuracy of the whole profile is desired. Hence, the true deviation model of torus is developed and then formulated as a minimax problem. Next, a relatively new and simple population based evolutionary approach, particle swarm optimization (PSO), is applied by imitating the social behavior of animals to find the minimum tolerance zone torusity. Simulated data with specified torusity zones are used to validate the deviation model. The torusity results are in close agreement with the actual torusity zones and also confirm the effectiveness of the proposed PSO when compared to those of the LSQ.

An Analysis on the Effect of the Government R&D Subsidies on the Private R&D Investments : in the Case of the Pharmaceutical Industry (정부 R&D 지원의 기업 R&D 투자에 대한 효과 분석 -제약산업을 중심으로-)

  • SaKong, Jin;Shin, You-Won
    • Health Policy and Management
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    • v.20 no.1
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    • pp.183-203
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    • 2010
  • The purpose of this study is to analyze the effect of the R&D subsidies by the government on the private firms' R&D investments in the Korean pharmaceutical industry, which are supposed to have positive effects on their economic performance. We also estimate the relationship between the private firms' R&D investments and firms' economic outcome. Empirical analysis is done by Error Component 2 Stage Least Squares(EC2SLS) estimation using 43 pharmaceutical firms' 8 years' panel data. The elasticity of the government R&D subsidies on the private R&D investments is 0.021%, which we cannot say 'efficient'. Also R&D investments have positive effects on the economic outcome of the pharmaceutical firms, as we expected. We propose several suggestions in the conclusion for the efficient way of government R&D subsidies to induce more private R&D investments.

Estimation of Demand Functions for Imported Fisheries Products Using Cointegration Analysis: Effect Analysis of Tariff Reduction (공적분 분석을 이용한 우리나라 수입수산물의 수요함수 추정 : 관세감축영향분석)

  • Nam, Jong-Oh;Kim, Soo-Jin
    • Ocean and Polar Research
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    • v.32 no.1
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    • pp.23-40
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    • 2010
  • This study investigated the effects of imported fisheries products on WTO/DDA tariff negotiations. To calculate the results, the study estimated the demand functions of imported fisheries products by using unit root and cointegration approaches. These approaches allowed us to solve spurious regression problems with macro-economic variables. In addition, this study surmised the effects of change by individually imported fish products from a tariff negotiation model using price elasticities of estimated import demand function. In a process of the analysis for estimating import effects, this study found out that 39 out of 128 imported fish products had positive (+) price elasticities or did not exhibit cointegrations. To cure this problem, this study suggested that the effects of these 39 imported products be estimated with the average variation rate of import volume, rather than by the Ordinary Least Squares approach. In this study, a case-study of tariff formula with coefficient 8 based on a 'Swiss formula' for priority duty rate of 2001 and 2008 was used by to analyze the effect of change in the 128 imported fish products of both years, respectively.