Seventh spectrum of tin: Sn VII

1984 ◽  
Vol 62 (2) ◽  
pp. 167-177 ◽  
Author(s):  
Th. A. M. VanKleef ◽  
Y. N. Joshi
Keyword(s):  
Least Squares ◽  
Energy Parameter ◽  
Grazing Incidence ◽  
Least Squares Fit

The seventh spectrum of tin was photographed in the 200–550-Å region on a 6.65-m grazing incidence spectrograph at the Zeeman Laboratory in Amsterdam. The source used was a triggered spark. The new observations have led us to analyze the 4d8–4d75p transitions in the Sn VII spectrum. All nine levels of the 4d8 configuration and 97 of 110 levels of the 4d75p configuration have been established. The least-squares-fit energy parameter calculations support the analysis. Two hundred and twenty-one lines have been classified in this spectrum.

Mark IV "Grasshopper" grazing incidence monochromator for the Canadian Synchrotron Radiation Facility (CSRF)

1982 ◽  
Vol 60 (2) ◽  
pp. 131-136 ◽  
Author(s):  
K. H. Tan ◽  
G. M. Bancroft ◽  
L. L. Coatsworth ◽  
B. W. Yates
Keyword(s):  
Synchrotron Radiation ◽  
Least Squares ◽  
Radiation Source ◽  
Ultrahigh Vacuum ◽  
Nonlinear Least Squares ◽  
Grazing Incidence ◽  
Zero Order ◽  
Optical Characteristics ◽  
Least Squares Fit ◽  
Absorption Edges

The vacuum, mechanical, and optical characteristics of a "Grasshopper" grazing incidence monochromator, for use with a synchrotron radiation source in the 30–300 eV range, is described. The monochromator is compatible with ultrahigh vacuum (≤ 5 × 10−10 Torr throughout), and the motor driven scan mechanism is linear and reliable. The monochromator has been calibrated using several known absorption edges between 36 and 102 eV and a nonlinear least squares fit to the scan equation. These same absorption edges, plus a scan over zero order, show that the present resolution of the monochromator (with 10 and 16 μm exit and entrance slits respectively) is 0.16 Å (0.06 eV at the Al L2.3 edge). With 10 μm entrance and exit slits, the resolution will be very close to the theoretical Δλ = 0.083 Å.

Changes in total body calcium balance with exercise in the rat

1983 ◽  
Vol 55 (1) ◽  
pp. 201-204 ◽  
Author(s):  
A. D. LeBlanc ◽  
H. J. Evans ◽  
P. C. Johnson ◽  
S. Jhingran
Keyword(s):  
Least Squares ◽  
Voluntary Exercise ◽  
Calcium Balance ◽  
Sprague Dawley ◽  
Total Body Calcium ◽  
Sprague Dawley Rats ◽  
Least Squares Fit ◽  
Significant Change ◽  
Total Body ◽  
And Control

The purpose of this study was to evaluate the effect of deconditioning on the total body calcium in rats. Two separate experiments were performed using female Sprague-Dawley rats, 187-266 days of age. Total body calcium was measured in experimental and control rats during and following several weeks of voluntary exercise. The slope from the least-squares fit of total body calcium with time was used to obtain an average calcium balance for each animal during each study period. In both groups the exercised rats had a significantly decreased calcium balance after cessation of exercise, whereas no significant change was seen in nonexercised controls. In both groups, the exercised animals gained calcium at a significantly greater rate than controls. Our findings indicate that while exercised rats may gain calcium at a faster rate compared with nonexercising controls, the rate of gain following cessation of exercise is less than the controls.

Estimation of the free core nutation period by the sliding-window complex least-squares fit method

2016 ◽  
Vol 57 (10) ◽  
pp. 2136-2140 ◽  
Author(s):  
Yonghong Zhou ◽  
Qiang Zhu ◽  
David A. Salstein ◽  
Xueqing Xu ◽  
Si Shi ◽  
...  
Keyword(s):  
Least Squares ◽  
Sliding Window ◽  
Free Core Nutation ◽  
Least Squares Fit

scholarly journals A Robust Regression by Using Huber Estimator and Tukey Bisquare Estimator for Predicting Availability of Corn in Karanganyar Regency, Indonesia

2018 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
Hasih Pratiwi ◽  
Yuliana Susanti ◽  
Sri Sulistijowati Handajani
Keyword(s):  
Least Squares ◽  
Robust Regression ◽  
Likelihood Estimation ◽  
Corn Production ◽  
Least Squares Fit ◽  
Class Of Estimators ◽  
M Estimation ◽  
Heavy Tailed ◽  
Least Squares Estimates ◽  
Huber Estimator

Linear least-squares estimates can behave badly when the error distribution is not normal, particularly when the errors are heavy-tailed. One remedy is to remove influential observations from the least-squares fit. Another approach, robust regression, is to use a fitting criterion that is not as vulnerable as least squares to unusual data. The most common general method of robust regression is M-estimation. This class of estimators can be regarded as a generalization of maximum-likelihood estimation. In this paper we discuss robust regression model for corn production by using two popular estimators; i.e. Huber estimator and Tukey bisquare estimator.<br />Keywords : robust regression, M-estimation, Huber estimator, Tukey bisquare estimator

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