Study of optimum discrete estimators in measurement analysis

Study of statistical techniques for obtaining estimates of true data parameters uses discrete measured quantities containing random error. These techniques develop estimation procedures as an iterative algorithm for digital computation in real time

Methods for injection error analysis and their comparison Scientific report no. 13

Formulation of direct and adjoint methods of trajectory injection error in vector matrix notation and compariso

The Pseudogap in La(2-x)Sr(x)CuO(4): A Raman Viewpoint

We report the results of Raman scattering experiments on single crystals of La(2-x)Sr(x)CuO(4) [La214] as a function of temperature and doping. In underdoped compounds low-energy B1g spectral weight is depleted in association with the opening of a pseudogap on regions of the Fermi surface located near (pi, 0) and (0, pi). The magnitude of the depletion increases with decreasing doping, and in the most underdoped samples, with decreasing temperature. The spectral weight that is lost at low-energies (omega < 800 cm-1) is transferred to the higher energy region normally occupied by multi-magnon scattering. From the normal state B2g spectra we have determined the scattering rate Gamma(omega, T) of qausiparticles located near the diagonal directions in k-space, (pi/2, pi/2) regions. In underdoped compounds, Gamma(omega, T) is suppressed at low temperatures for energies less than Eg(x) ~ 800 cm-1. The observed doping dependence of the two-magnon scattering and the scattering rate suppression thus suggest that the pseudogap is characterized by an energy scale Eg ~ J, where J is the antiferromagnetic super-exchange energy. Comparison with the results from other techniques provides a consistent picture of the pseudogap in La214.Comment: 6 pages, 5 figures, minor revisions include correct form of the B2g Raman response function and new figures of the recalculated B2g scattering rate. Presented at the APS March99 Meeting, accepted for publication in the Canadian Journal of Physic

Results from tests, with van-mounted sensor, of magnetic leader cable for aircraft guidance during roll-out and turnoff

Tests were conducted with a van mounted experimental magnetic leader cable sensor to evaluate its potential for measuring aircraft displacement and heading with respect to the leader cable during roll out and turnoff. Test results show that the system may be usable in measuring displacement but the heading measurement contains errors introduced by distortion of the magnetic field by the metal van or aircraft

Can the frequency-dependent specific heat be measured by thermal effusion methods?

It has recently been shown that plane-plate heat effusion methods devised for wide-frequency specific-heat spectroscopy do not give the isobaric specific heat, but rather the so-called longitudinal specific heat. Here it is shown that heat effusion in a spherical symmetric geometry also involves the longitudinal specific heat.Comment: Paper presented at the Fifth International Workshop on Complex Systems (Sendai, September, 2007), to appear in AIP Conference Proceeding

CROP INSURANCE VALUATION UNDER ALTERNATIVE YIELD DISTRIBUTIONS

Considerable disagreement exists about the most appropriate characterization of farm-level yield distributions. Yet, the economic importance of alternate yield distribution specifications on insurance valuation, product designs and farm-level risk management has not been investigated or documented. The results of this study demonstrate that large differences in expected payments from popular crop insurance products can arise solely from the parameterization chosen to represent yields. The results suggest that the frequently unexamined yield distribution specification may lead to incorrect conclusions in important areas of insurance and risk management research such as policy rating, and assessment of expected payments from policies.Risk and Uncertainty,

ESTIMATING FARM-LEVEL YIELD DISTRIBUTIONS FOR CORN AND SOYBEANS IN ILLINOIS

Many yield modeling approaches have been developed in attempts to provide accurate characterizations of farm-level yield distributions due to the importance of yield uncertainty in crop insurance design and rating, and for managing farm-level risk. Competing existing models of crop yields accommodate varying skewness, kurtosis, and other departures from normality including features such as multiple modes. Recently, the received view of crop yield modeling has been challenged by Just and Weninger who indicate that there is insufficient evidence to reject normality given data limitations and potential methodological shortcomings in controlling for deterministic components (trend) in yields. They point out that past empirical efforts to estimate and validate specific-farm distributional characterizations have been severely hampered by data limitations. As a result, they argue in favor of normality as an appropriate parameterization of crop yields. This paper investigates alternate representations of farm-level crop yield distributions using a unique data set from the University of Illinois Endowment farms, containing same-site yield observations for a relatively long period of time, and under conditions that closely mirror actual farm conditions in Illinois. Results from alternate econometric model specifications controlling for trend effects suggest that a linear trend provides an adequate representation of crop yields at the farm level during the period covered by the estimations. Specification tests based on a linear-trend model suggest significant heteroskedasticity is present in only a few farms, and that the residuals are white noise. With these data, Jarque-Bera normality test results indicate that normality of detrended yield residuals is rejected by a far greater number of fields than would be explained due to randomness. Thus, to further clarify the issue of yield distribution characterizations, more complete goodness-of-fit measures are compared across a larger set of candidate distributions. The results indicate that the Weibull distribution consistently ranks better than the normal distribution both in fields where normality is rejected and in fields where normality is not rejected. The results highlight the fact that failing to reject normality is not the same as identifying normality as a "best" parameterization, and provide guidance for progressing toward better representations of farm-level crop yields.Productivity Analysis, Research Methods/ Statistical Methods, Teaching/Communication/Extension/Profession,