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Alternatives to sampling-theory stratified and regression estimators of crop production and timber biomass were examined. An alternative estimator which is viewed as especially promising is the errors-in-variable regression estimator. Investigations established the need for caution with this estimator when the ratio of two error variances is not precisely known.
Several statistical and information criteria need to be considered when selecting an adequate model. Incorrect stability and control derivates result from inadequate aerodynamic model structure. Stepwise regression is used to determine the structure for an adequate model. Flight data which covers a nonlinear aerodynamic model range may be analyzed as a single data set or partitioned into several distinct sets. Stepwise regression for model structure detemination and parameter estimation was successfully applied to three aircraft types (single engine general aviation, unaugmented modern jet fighter, jet transport).
A combined physical statistical method for the retrieval of atmospheric water vapor column densities has been developed at the Goddard Laboratory for Atmospheric Sciences. In this method differences between observed and calculated clear column brightness temperatures are used in a regression formalism to obtain estimates of integrated column densities in given atmospheric layers. The physics of the radiative transfer problem is contained in the calculated clear column brightness temperatures and in accounting for the effects of clouds on the observed radiances. The regression matrix is equivalent to a set of empirical sensitivity factors.
On the basis of cycles 8 through 20, spanning about 143 years, observations of sunspot number, smoothed sunspot number, and their temporal properties were used to compute means, standard deviations, ranges, and frequency of occurrence histograms for a number of sunspot cycle parameters. The resultant schematic sunspot cycle was contrasted with the mean sunspot cycle, obtained by averaging smoothed sunspot number as a function of time, tying all cycles (8 through 20) to their minimum occurence date. A relatively good approximation of the time variation of smoothed sunspot number for a given cycle is possible if sunspot cycles are regarded in terms of being either HIGH- or LOW-R(MAX) cycles or LONG- or SHORT-PERIOD cycles, especially the latter. Linear regression analyses were performed comparing late cycle parameters with early cycle parameters and solar cycle number. The early occurring cycle parameters can be used to estimate later occurring cycle parameters with relatively good success, based on cycle 21 as an example. The sunspot cycle record clearly shows that the trend for both R(MIN) and R(MAX) was toward decreasing value between cycles 8 through 14 and toward increasing value between cycles 14 through 20. Linear regression equations were also obtained for several measures of solar activity.
The geometric quality of TM film and digital products is evaluated by making selective photomeasurements and by measuring the coordinates of known features on both the TM products and map products. These paired observations are related using a standard linear least squares regression approach. Using regression equations and coefficients developed from 225 (TM film product) and 20 (TM digital product) control points, map coordinates of test points are predicted. The residual error vectors and analysis of variance (ANOVA) were performed on the east and north residual using nine image segments (blocks) as treatments. Based on the root mean square error of the 223 (TM film product) and 22 (TM digital product) test points, users of TM data expect the planimetric accuracy of mapped points to be within 91 meters and within 117 meters for the film products, and to be within 12 meters and within 14 meters for the digital products.
Statistical analysis and multiple regression were used to determine and quantify the significant hygrothermomechanical variables which influence the tensile durability/life (cycle loading, fatigue) of boron-fiber/epoxy-matrix (B/E) and high-modulus-fiber/epoxy-matrix (HMS/E) composites. The use of the multiple regression analysis reduced the variables from fifteen, assumed initially, to six or less with a probability of greater than 0.999. The reduced variables were used to derive predictive models for compression and intralaminar shear durability/life of B/E and HMS/E composites assuming isoparametric fatigue behavior. The predictive models were subsequently generalized to predict the durability/life of graphite/fiber-r generalized model is of simple form, predicts conservative values compared with measured data and should be adequate for use in preliminary designs. Previously announced in STAR as N82-14287
The use of LANDSAT multispectral scanner digital data for multi-crop acreage estimation in the central Snake River Plain of Idaho was examined. Two acquisitions of LANDSAT data covering ground sample units selected from a U.S. Department of Agriculture sampling frame in a four country study site were used to train a maximum likelihood classifier which, subsequently, classified all picture elements in the study site. Acreage estimates for six major crops, by county and for the four counties combined, were generated from the classification using the Battesse-Fuller model for estimation by regression in small areas. Results from the regression analysis were compared to those obtained by direct expansion of the ground data. Using the LANDSAT data significantly decreased the errors associated with the estimates for the three largest acreage crops. The late date of the second LANDSAT acquisition may have contributed to the poor results for three summer crops.
Data from SCR-B on Nimbus 5 have been processed to yield global, orbital temperatures at 10, 5, 2, 1, and 0.4 mb for the period January 1977 through April 1978 under the current task. In addition gridded values at 10 deg latitude by 20 deg longitude were prepared by space-time interpolation for the period January 1975 through April 1978. Temperature retrieval was based on regression of radiances against Meteorological Rocket Network data, with regressions recomputed at approximately six-month intervals. This data now completes a consistent time series from April 1970 to April 1978 for all available radiance data from SCR A and SCR B on Nimbus 4 and 5. The processing details for the current period are discussed, but is also applicable to the previous data periods. The accuracy of the temperature retrievals for each 6-month period for the entire eight years is given in the Appendices.
A procedure is developed for estimating sea surface temperatures from multispectral image data acquired from the VISSR atmospheric sounder on the geostationary GOES satellites. Theoretical regression equations for two and three infrared window channels are empirically tuned using clear field of view satellite radiances matched with reports of SST from NOAA fixed environmental buoys. The empirical regression equations are then used to produce daily regional analyses of SST. Monthly mean SST's for the western North Atlantic and the eastern equatorial Pacific during March and July 1982 were produced for use in the SST Intercomparison Workshop Series. Workshop results showed VAS SST's have a scatter of 0.8-1.0 C and a slight warm bias with respect to the other measurements of SST. The VAS SST's show no discernible bias in the region of El Chichon volcanic aerosol cloud.
The relation of cosmic ray intensity to solar wind velocity is investigated, using neutron monitor data from Kiel and Deep River. The analysis shows that the regression coefficient of the average intensity for a time interval to the corresponding average velocity is negative and that the absolute effect increases monotonously with the interval of averaging, tau, that is, from -0.5% per 100km/s for tau = 1 day to -1.1% per 100km/s for tau = 27 days. For tau 27 days the coefficient becomes almost constant independently of the value of tau. The analysis also shows that this tau-dependence of the regression coefficiently is varying with the solar activity.
An event is reported of approx. 37 min periodicity in cosmic ray intensity observed at Akeno(38 deg 47 N, 138 deg 30 E. 900m above s.l., cutoff 10.4 GV) during 1300 approx. 1900 UT on April 25th, 1984, just a day before Forbush decrease of April 26th. This event seemed to be followed by the periodic variations of the geomagnetic field observed at Kakioka (36 deg 23 N, 140 deg 18 E). The regression coefficient between them was obtained approx. 0.07%/10nT. It is shown that in general the power spectral density of cosmic rays in the frequency of 0.0001 approx. 0.001Hz correlates positively with the fluctuations of geomagnetic field (Dst field) around approx. 1.2x0.0001Hz. From the analysis of 47 days data (April 14th to June 13th, 1984) the regression curve was obtained as y=0.275x sup 0.343 with the correlation coefficient of 0.48, where x and y mean Fourier components of Dst field summed over 1.04 approx. 1.39x0.001Hz and cosmic ray power spectral density averaged over 0.0001 approx. 0.001Hz.
Green leaf area index (LAI) is a measure of vegetative growth and development and is frequently used as an input parameter in yield estimation and evapotranspiration models. Extensive destructive sampling is usually required to achieve accurate estimates of green LAI in natural situations. In this investigation, a statistical modeling approach was used to predict the green LAI of oats from bidirectional reflectance data collected with multiband radiometers. Stepwise multiple regression models based on two sets of spectral reflectance factors accounted for 73 percent and 65 percent of the variance in green LAI of oats. Exponential models of spectral data transformations of greenness, normalized difference, and near-infrared/red ratio accounted for more of the variance in green LAI than the multiple regression models.
A simple statistical technique is described to determine monthly mean marine surface-layer humidity, which is essential in the specification of surface latent heat flux, from total water vapor in the atmospheric column measured by space-borne sensors. Good correlation between the two quantities was found in examining the humidity soundings from radiosonde reports of mid-ocean island stations and weather ships. The relation agrees with that obtained from satellite (Seasat) data and ship reports averaged over 2 deg areas and a 92-day period in the North Atlantic and in the tropical Pacific. The results demonstrate that, by using a local regression in the tropical Pacific, total water vapor can be used to determine monthly mean surface layer humidity to an accuracy of 0.4 g/kg. With a global regression, determination to an accuracy of 0.8 g/kg is possible. These accuracies correspond to approximately 10 to 20 W/sq m in the determination of latent heat flux with the bulk parameterization method, provided that other required parameters are known.
Abstract- Digital techniques for separation of luminance and chrominance components from composite NTSC broadcast television signals are explored. First, comb filters are introduced. Secondly, filters based on linear regression are developed. Finally, a third filtering form, the allpass filter is considered. Techniques are compared based on mean squared error criteria and subjective testing. It is demonstrated that the allpass filtering technique is superior to both the comb filtering as well as the regression filtering.
Statistical procedures taken from the field of survival analysis have been adapted to astronomical usage and have been applied to a sample of stars in the B-V color range between 0.1 and 0.5 with measured soft X-ray luminosities and projected equatorial velocities. The two-sample problem and linear regression problem with arbitrarily censored data were studied. A new method for determining the linear regression between two random variables in the presence of arbitrary censoring has been developed which can also be used for a likelihood-ratio test for the independence of two random variables and for principal-component analysis in the presence of arbitrary censoring. The required numerical computations can be carried out straightforwardly and rapidly.
The mesoscale accuracy of GOES Visible/IR Spin-Scan-Radiometer (VISSR) Atmospheric Sounder (VAS) temperature profiles and mean-precipitable-water measurements obtained over central Texas on March 6, 1982, is evaluated on the basis of comparing them with three-hourly rawinsonde data (up to 100 mbar) of similar spatial resolution for the same area and time. The VAS data comprise three sets: physical retrievals by the method of Smith (1970), modified physical retrievals by the method of Smith (1983), and regression soundings (incorporating some rawinsonde data) by the method of Lee et al. (1983). The data are presented graphically, and all three VAS data sets are found to have similar temperature biases, which vary from hot to cold with altitude and are apparently related to major inversions. Systematic moisture biases are seen in the physical and modified physical data sets, while the regression soundings are relatively unbiased but do not accurately reproduce moisture gradients seen in the rawinsonde data.
The vibration and performance optimization procedure using regression analysis was successfully applied to an advanced aeroelastic blade design study. The major advantage of this regression technique is that multiple optimizations can be performed to evaluate the effects of various objective functions and constraint functions. The data bases obtained from the rotorcraft flight simulation program C81 and Myklestad mode shape program are analytically determined as a function of each design variable. This approach has been verified for various blade radial ballast weight locations and blade planforms. This method can also be utilized to ascertain the effect of a particular cost function which is composed of several objective functions with different weighting factors for various mission requirements without any additional effort.
The successful parametric modeling of the aerodynamics for an airplane operating at high angles of attack or sideslip is performed in two phases. First the aerodynamic model structure must be determined and second the associated aerodynamic parameters (stability and control derivatives) must be estimated for that model. The purpose of this paper is to document two versions of a stepwise regression computer program which were developed for the determination of airplane aerodynamic model structure and to provide two examples of their use on computer generated data. References are provided for the application of the programs to real flight data. The two computer programs that are the subject of this report, STEP and STEPSPL, are written in FORTRAN IV (ANSI l966) compatible with a CDC FTN4 compiler. Both programs are adaptations of a standard forward stepwise regression algorithm. The purpose of the adaptation is to facilitate the selection of a adequate mathematical model of the aerodynamic force and moment coefficients of an airplane from flight test data. The major difference between STEP and STEPSPL is in the basis for the model. The basis for the model in STEP is the standard polynomial Taylor's series expansion of the aerodynamic function about some steady-state trim condition. Program STEPSPL utilizes a set of spline basis functions.