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PubMed2000

Additive genetic parameter estimates for heifer pregnancy and subsequent reproduction in Angus females.

A primary objective of this study was to determine whether the binary traits heifer pregnancy (HP) and subsequent rebreeding (SR) were heritable in an experimental population of Angus cattle. A second objective was to determine the nature of the additive genetic relationships among HP, SR, and stayability (S(5/1)) in the same population. Heifer pregnancy was defined as the observation of a heifer conceiving and remaining pregnant to palpation at 120 d, given exposure during the breeding season. Subsequent rebreeding was defined as the observation of a 2-yr-old conceiving and remaining pregnant to palpation at 105 d, given pregnancy as a yearling and exposure during the breeding season. Stayability was defined as the probability of a female having at least five calves, given she becomes a dam as a 2 yr old. Data were analyzed using a maximum a posteriori probit threshold model to predict breeding values on the liability scale and Method R procedures to estimate variance components in the determination of heritability (h2). Additive genetic groups were used in determining the additive genetic relationships among these fertility traits. Additive genetic groups were formed on one trait's breeding values and used in the prediction of another trait's breeding values. Analyses yielded h2 estimates that were out of the parameter space 8.5 and 46.3% for HP and SR, respectively, and 5.9% for the reestimation of S(5/1). The majority of point estimates outside the parameter space for SR converged toward 0, whereas those for HP and S(5/1) primarily converged toward 1. From the subsamples producing h2 estimates within the parameter space, average h2 for HP, SR, and S(5/1) were .21, .19, and .15, with standard deviations of .12, .14, and .08, respectively. The estimates of h2 indicate that HP and S(5/1) were heritable and should respond favorably to selection; however, SR did not appear heritable due to the large number of subsamples producing h2 estimates out of the parameter space. Fixed effect estimates for age of dam were significant for HP. From the analyses using additive genetic groups, the relationship among HP and S(5/1) appeared to be nonlinear. This potential nonlinear relationship seen between HP and S(5/1) indicates that selection for improved female fertility would be most effective by having predictions on both traits.

Animals↗

PubMed1998

Variability of some SEMG parameter estimates with electrode location.

Muscular action potential conduction velocity (CV) and mean power frequency (MPF) are commonly used parameters to describe the surface electromyographic signal (SEMG). The discrepancies concerning the behavior and interpretation of these main parameters in the literature have motivated this work. Our objective was to evaluate within- and between-individual reproducibility, sensitivity and variation of CV and MPF depending on the electrode location with respect to various contraction modalities. The results present evidence for significant influence of electrode location on CV and MPF, not only in their initial values but also in their changes during fatiguing efforts. This influence appears to be subject-dependent. This variability seems to be essentially due to the relative displacements of myotendinous and neuromuscular junctions with respect to the electrode set. Moreover, this study shows that MPF can be seen as force-dependent under certain conditions and that the CV-MPF relationship is strongly influenced by methodological factors. In conclusion, it seems irrelevant to derive reliable SEMG parameter estimates without considering electrode location. There is a strong need for proper standardization based on anatomical and methological aspects before attempting any individual characterization. Finally, we suggest a procedure for assessment of measurement quality.

Action Potentials↗

PubMed1989

The influence of assay variability on pharmacokinetic parameter estimation.

The impact of assay variability on pharmacokinetic modeling was investigated. Simulated replications (150) of three "individuals" resulted in 450 data sets. A one-compartment model with first-order absorption was simulated. Random assay errors of 10, 20, or 30% were introduced and the ratio of absorption rate (Ka) to elimination rate (Ke) constants was 2, 10, or 20. The analyst was blinded as to the rate constants chosen for the simulations. Parameter estimates from the sequential method (Ke estimated with log-linear regression followed by estimation of Ka) and nonlinear regression with various weighting schemes were compared. NONMEM was run on the 9 data sets as well. Assay error caused a sizable number of curves to have apparent multicompartmental distribution or complex absorption kinetic characteristics. Routinely tabulated parameters (maximum concentration, area under the curve, and, to a lesser extent, mean residence time) were consistently overestimated as assay error increased. When Ka/Ke = 2, all methods except NONMEM underestimated Ke, overestimated Ka, and overestimated apparent volume of distribution. These significant biases increased with the magnitude of assay error. With improper weighting, nonlinear regression significantly overestimated Ke when Ka/Ke = 20. In general, however, the sequential approach was most biased and least precise. Although no interindividual variability was included in the simulations, estimation error caused large standard deviations to be associated with derived parameters, which would be interpreted as interindividual error in a nonsimulation environment. NONMEM, however, acceptably estimated all parameters and variabilities. Routinely applied pharmacokinetic estimation methods do not consistently provide unbiased answers. In the specific case of extended-release drug formulations, there is clearly a possibility that certain estimation methods yield Ka and relative bioavailability estimates that would be imprecise and biased.

Biometry↗

PubMed1991

In vivo NMR spectral parameter estimation: a comparison between time and frequency domain methods.

We have compared various methods of in vivo NMR spectral parameter estimation, namely a nonlinear fit of the free induction decay signal in the time domain (NLTD), a nonlinear fit of the fast Fourier transform of the FID data in the frequency domain using either a continuous Lorentzian model (NLLM) or a Fourier-sampled model (NLFM), and a time-domain linear prediction method using singular value decomposition (LPSVD). Monte Carlo simulations of 31P and 13C in vivo experiments were used to assess the bias and statistical uncertainties of spectral parameters obtained with each method. In the 31P case, all methods appear to be equivalent except the LPSVD method that led to significantly biased peak amplitudes (up to 28%). In the 13C case, the only methods able to recover the glycogen peak were the NLTD method and its equivalent in the frequency domain (NLFM). In both the 31P and the 13C cases simulations demonstrated that 256 data points were sufficient. These results demonstrate the feasibility and the robustness of a nonlinear fit of the FID data in the time domain, and we illustrate this on 31P and 13C data sets obtained in humans.

Algorithms↗

PubMed1987

A note on confidence intervals with extended least squares parameter estimates.

It has previously been shown that the extended least squares (ELS) method for fitting pharmacokinetic models behaves better than other methods when there is possible heteroscedasticity (unequal error variance) in the data. Confidence intervals for pharmacokinetic parameters, at the target confidence level of 95%, computed in simulations with several pharmacokinetic and error variance models, using a theoretically reasonable approximation to the asymptotic covariance matrix of the ELS parameter estimator, are found to include the true parameter values considerably less than 95% of the time. Intervals with the ordinary least squares method perform better. Two adjustments to the ELS confidence intervals, taken together, result in better performance. These are: (i) apply a bias correction to the ELS estimate of variance, which results in wider confidence intervals, and (ii) use confidence intervals with a target level of 99% to obtain confidence intervals with actual level closer to 95%. Kineticists wishing to use the ELS method may wish to use these adjustments.

Kinetics↗

PubMed1984

Parameter estimation using the quasi-linear viscoelastic model proposed by Fung.

Using the quasi-linear viscoelastic model proposed by Fung for the description of the viscoelastic properties of soft biological tissues, the parameters governing their time-dependent behavior are commonly estimated from relaxation experiments. Exact quantification is possible from the response to a step change in the strain. Since it is physically impossible to realize a true step change in the strain, in practice the response to a steplike strain change is used. In the present study the discrepancies between the exact and the estimated parameter values are investigated using a hypothetical quasi-linear viscoelastic material. The parameter tau 1, governing the fast viscous phenomena, is found to be subject to the largest errors. Methods for obtaining better estimates of tau 1 are outlined in a number of special cases.

Biomedical Engineering↗

PubMed1998

Spectral parameter estimation by an iterative quadratic maximum likelihood method.

An iterative quadratic maximum likelihood (IQML) method is applied to spectral parameter estimation of 1D NMR data. A careful comparison of the linear prediction (LP) method based on the singular value decomposition, the total least squares (TLS) method, and IQML has clearly demonstrated that IQML is superior to both the LP and TLS methods in terms of the accuracy and bias of the estimation. The superiority of the IQML method lies in the fact that constraints on the NMR signal can easily be incorporated into the iterative process. The iterative quadratic maximum likelihood method can be used to analyze NMR data directly or to provide a starting point for further data refinement.

Algorithms↗

PubMed1991

Investigation of parameter estimator and adaptive controller for assist pump by computer simulation.

The multi-output adaptive controller of a left ventricular assist device (LVAD) was studied by computer simulation. The controller regulated two outputs--mean aortic pressure (mAoP) and mean atrial pressure (mLAP)--by regulating vacuum pressure (input). The autoregressive models were used to describe the circulatory system. The parameters of the models were estimated by the recursive least squares method. Based on the autoregressive models, the vacuum pressure minimizing a performance index was searched. The index used was the weighted summation of the square errors. Responses of the adaptive controller were simulated when the contractility of the left ventricle was decreased at various rates and the peripheral resistance was changed. Both the mAoP and mLAP were controlled to their predicted values in the steady state. The steady-state errors of the mAoP were less than a few mm Hg, and those of the mLAP were lower than 1 mm Hg. Consequently, the estimated parameters can be regarded as true parameters, and the adaptive controller has the potential to control more than two outputs. The multioutput adaptive controller studied is useful in controlling the LVAD according to the change in circulatory condition.

Aorta, Thoracic↗

PubMed1994

Regurgitant volume in aortic regurgitation from a parameter estimation procedure.

The regurgitant volume and regurgitant orifice area as well as total peripheral resistance and arterial compliance were estimated in a cardiovascular hydromechanical simulator and in 10 patients with aortic regurgitation. A parameter estimation procedure based on a simple model of the cardiovascular system, Doppler measurements of the regurgitant jet, aortic systolic flow, and systolic and diastolic blood pressures was used. In the cardiovascular simulator the estimated regurgitant orifice area was compared with the size of a hole in the disk of a mechanical aortic valve. In the patients the regurgitant fraction was compared with semiquantitative grading from echocardiography routinely performed in our laboratory. In the hydromechanical simulator, the estimated regurgitant orifice area of 26.5 +/- 3.5 (SD) mm2 (n = 9) was not different from the true value of 24 mm2. In the patients there was a fair relationship between the estimated regurgitant fraction and the semiquantitative grading. The estimated regurgitant orifice areas varied between 1.6 and 31.2 mm2. The estimated mean values of total peripheral resistance and arterial compliance were 1.67 +/- 0.55 mmHg.s.ml-1 and 1.30 +/- 0.42 ml/mmHg, respectively.

Adolescent↗

PubMed1999

Using nonlinear regression to estimate parameters of dark adaptation.

An objective technique for estimating the kinetics of dark adaptation is presented, with which one can evaluate models with multiple parameters, evaluate several models of dark adaptation simultaneously, and rapidly analyze large data sets. Another advantage is the ability to simultaneously estimate transition times and rates of sensitivity recovery. Finally, this nonlinear regression technique does not require that the distributional properties of the data be transformed, and thus, parameter estimates are in meaningful units and reflect the actual rate of recovery of sensitivity.

Adult↗

PubMed2001

Auto-SOM: recursive parameter estimation for guidance of self-organizing feature maps.

An important technique for exploratory data analysis is to form a mapping from the high-dimensional data space to a low-dimensional representation space such that neighborhoods are preserved. A popular method for achieving this is Kohonen's self-organizing map (SOM) algorithm. However, in its original form, this requires the user to choose the values of several parameters heuristically to achieve good performance. Here we present the Auto-SOM, an algorithm that estimates the learning parameters during the training of SOMs automatically. The application of Auto-SOM provides the facility to avoid neighborhood violations up to a user-defined degree in either mapping direction. Auto-SOM consists of a Kalman filter implementation of the SOM coupled with a recursive parameter estimation method. The Kalman filter trains the neurons' weights with estimated learning coefficients so as to minimize the variance of the estimation error. The recursive parameter estimation method estimates the width of the neighborhood function by minimizing the prediction error variance of the Kalman filter. In addition, the "topographic function" is incorporated to measure neighborhood violations and prevent the map's converging to configurations with neighborhood violations. It is demonstrated that neighborhoods can be preserved in both mapping directions as desired for dimension-reducing applications. The development of neighborhood-preserving maps and their convergence behavior is demonstrated by three examples accounting for the basic applications of self-organizing feature maps.

Algorithms↗

PubMed1993

A simple computational approach to model parameter estimation.

The desire to describe biological data using mathematical models has led to the rapid development of various analytical techniques for model identification and parameter estimation. The procedures used may be non-linear and complex, and require long calculation periods. Thus, the aid of a personal computer renders efficient the application of these rather complicated procedures. In this study we developed a simple identification programme for heparan sulfate pharmacodynamics which can be easily and rapidly implemented on a personal computer. The programme is based on an iterative algorithm performing a non-linear regression analysis by the least-square method. This programme was applied to a clinical measured variables with which it was possible to quantify the pharmacodynamic effect of heparan sulfate.

Aged↗

PubMed1993

Reconstruction of experimental hyperthermia temperature distributions: application of state and parameter estimation.

Subsets of data from spatially sampled temperatures measured in each of nine experimental heatings of normal canine thighs were used to test the feasibility of using a state and parameter estimation (SPE) technique to predict the complete measured data set in each heating. Temperature measurements were made at between seventy-two and ninety-six stationary thermocouple locations within the thigh, and measurements from as few as thirteen of these locations were used as inputs to the estimation algorithm. The remaining (non "input") measurements were compared to the predicted temperatures for the corresponding "unmeasured" locations to judge the ability of the estimation algorithm to accurately reconstruct the complete experimental data set. The results show that the predictions of the "unmeasured" steady-state temperatures are quite accurate in general (average errors usually < 0.5 degrees C; and small variances about those averages) and that this reconstruction procedure can yield improved descriptors of the steady-state temperature distribution. The accuracy of the reconstructed temperature distribution was not strongly affected by either the number of perfusion zones or by the number of input sensors used by the algorithm. One situation extensively considered in this study modeled the thigh with twenty-seven independent regions of perfusion. For this situation, measurements from ninety-six to thirteen sensors were used as input to the estimation algorithm. The average error for all of these cases ranged from -0.55 degrees C to +0.75 degrees C, respectively, and was not strongly related to the number of sensors used as input to the estimation algorithm.(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗

PubMed1982

Parameter estimation of transpulmonary mechanics by a nonlinear inertive model.

Transpulmonary mechanics of anesthetized intubated dogs were studied during control breathing and hemorrhage-induced hyperventilation by least-mean-squares parameter estimation using several model versions. The classical elastance-resistance model was modified to include nonlinear elastic and viscous pressure terms with and without a linear inertive pressure component. Inclusion of the nonlinear terms decreased the root-mean-square error of fitting (q) of the classical model on the average to 67% in the control period and to 58% during hyperventilation. An additional decrease due to inertance was 4% (control) and 22% (hyperventilation) and was associated with acceptable estimates of inertance [0.056 +/- 0.02 (SD) and 0.063 +/- 0.008 cmH2O . l-1 . s2, respectively]. When inertance alone was added to the classical model, negligible improvement in q and unrealistic values of inertance were obtained. Conventional measures (Edyn and midvolume resistance) were close to the corresponding least-mean-squares estimates (E and R) of all model versions, except that in hyperventilation neglecting the inertance caused Edyn to markedly overestimate E of nonlinear inertive model.

Animals↗

PubMed2001

Parameter estimation procedure for complex non-linear systems: calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch.

When applied to large simulation models, the process of parameter estimation is also called calibration. Calibration of complex non-linear systems, such as activated sludge plants, is often not an easy task. On the one hand, manual calibration of such complex systems is usually time-consuming, and its results are often not reproducible. On the other hand, conventional automatic calibration methods are not always straightforward and often hampered by local minima problems. In this paper a new straightforward and automatic procedure, which is based on the response surface method (RSM) for selecting the best identifiable parameters, is proposed. In RSM, the process response (output) is related to the levels of the input variables in terms of a first- or second-order regression model. Usually, RSM is used to relate measured process output quantities to process conditions. However, in this paper RSM is used for selecting the dominant parameters, by evaluating parameters sensitivity in a predefined region. Good results obtained in calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch proved that the proposed procedure is successful and reliable.

Automation↗

PubMed1976

CSTRIP, a fortran IV computer program for obtaining initial polyexponential parameter estimates.

A new exponential stripping program, CSTRIP, has been developed. This program overcomes the problems associated with the use of previously published techniques and enables the rapid economical calculation of initial polyexponential parameter estimates. Values for the coefficients and exponents of the exponential terms are calculated as well as estimates of lag times. An exhaustive search procedure ensures that the results are comparable to, or better than, those obtained by manual residual methods.

Computers↗

PubMedDate not supplied

Detection and parameter estimation for quantitative trait loci using regression models and multiple markers.

A strategy of multi-step minimal conditional regression analysis has been developed to determine the existence of statistical testing and parameter estimation for a quantitative trait locus (QTL) that are unaffected by linked QTLs. The estimation of marker-QTL recombination frequency needs to consider only three cases: 1) the chromosome has only one QTL, 2) one side of the target QTL has one or more QTLs, and 3) either side of the target QTL has one or more QTLs. Analytical formula was derived to estimate marker-QTL recombination frequency for each of the three cases. The formula involves two flanking markers for case 1), two flanking markers plus a conditional marker for case 2), and two flanking markers plus two conditional markers for case 3). Each QTL variance and effect, and the total QTL variance were also estimated using analytical formulae. Simulation data show that the formulae for estimating marker-QTL recombination frequency could be a useful statistical tool for fine QTL mapping. With 1,000 observations, a QTL could be mapped to a narrow chromosome region of 1.5 cM if no linked QTL is present, and to a 2.8 cM chromosome region if either side of the target QTL has at least one linked QTL.

Journal Article↗

PubMed2004

Determining the slow crack growth parameter and Weibull two-parameter estimates of bilaminate disks by constant displacement-rate flexural testing.

OBJECTIVES: This study examined the influence of displacement-rate and relative layer heights (RLH) on the slow crack growth exponent and Weibull two-parameter estimates of bilayered ceramic composite disks composed of In-Ceram Alumina and Vitadur Alpha porcelain. METHODS: Equibiaxial disks were fabricated with RLH of 1:2, 1:1 and 2:1, for In-Ceram Alumina and Vitadur Alpha porcelain, respectively. Ninety specimens each (30 1:2, 30 1:1, and 30 2:1) were tested in an equibiaxial ring-on-ring testing apparatus at displacement-rates of 0.127, 1.27 and 12.7 mm min(-1). RESULTS: Weibull parameters were statistically significantly affected by changes in RLH at a constant displacement-rate and the slow crack growth parameters were significantly affected by RLH. Many specimens exhibited nonbrittle failure modes. Nonbrittle failures usually exhibited a fall, followed by a rise in load prior to catastrophic failure, and most occurred in specimens with thicker cores at low displacement-rates. SIGNIFICANCE: Geometries of layered materials may affect their reliability and longevity.

Aluminum Oxide↗