Non-Gaussian error distributions of galactic rotation speed measurements

被引:10
|
作者
Rajan, Ashwani [1 ]
Desai, Shantanu [2 ]
机构
[1] Indian Inst Technol, Dept Phys, Gauhati 781039, Assam, India
[2] Indian Inst Technol, Dept Phys, Hyderabad 502285, Telangana, India
来源
EUROPEAN PHYSICAL JOURNAL PLUS | 2018年 / 133卷 / 03期
关键词
MEDIAN STATISTICS; CO SURVEY; MASS;
D O I
10.1140/epjp/i2018-11946-7
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We construct the error distributions for the galactic rotation speed (Theta(0)) using 137 data points from measurements compiled in the paper by de Grijs and Bono (Astrophys. J. Suppl. Ser. 232, 22 (2017)), with all observations normalized to the galactocentric distance of 8.3 kpc. We then checked (using the same procedures as in the works by Ratra et al.) if the errors constructed using the weighted mean and the median as the estimate obey Gaussian statistics. We find using both these estimates that they have much wider tails than the Gaussian distribution. We also tried to fit the data to three other distributions: Cauchy, double-exponential, and Students-t. The best fit is obtained using the Students-t distribution for n = 2 using the median value as the central estimate, corresponding to a p-value of 0.1. We also calculate the median value of Theta(0) using all the data as well as using the median of each set of measurements based on the tracer population used. Because of the non-Gaussianity of the residuals, we point out that the subgroup median value, given by Theta(med) = 219.65 km/s, should be used as the central estimate for Theta(0).
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Non-Gaussian error distributions of galactic rotation speed measurements
    Ashwani Rajan
    Shantanu Desai
    The European Physical Journal Plus, 133
  • [2] NON-GAUSSIAN ERROR DISTRIBUTIONS OF LMC DISTANCE MODULI MEASUREMENTS
    Crandall, Sara
    Ratra, Bharat
    ASTROPHYSICAL JOURNAL, 2015, 815 (02):
  • [3] Non-Gaussian distributions
    Mastrangelo, M
    Mastrangelo, V
    Teuler, JM
    APPLIED MATHEMATICS AND COMPUTATION, 1999, 101 (2-3) : 99 - 124
  • [4] Non-gaussian distributions
    Mastrangelo, M
    Mastrangelo, V
    Teuler, JM
    APPLIED MATHEMATICS AND COMPUTATION, 2000, 109 (2-3) : 225 - 247
  • [5] Non-Gaussian error distribution of Hubble constant measurements
    Chen, G
    Gott, JR
    Ratra, B
    PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC, 2003, 115 (813) : 1269 - 1279
  • [6] Non-Gaussian error distribution of 7Li abundance measurements
    Crandall, Sara
    Houston, Stephen
    Ratra, Bharat
    MODERN PHYSICS LETTERS A, 2015, 30 (25)
  • [8] Integration of IMU in Indoor Positioning Systems with Non-Gaussian Ranging Error Distributions
    Li, Shenghong
    Hedley, Mark
    Collings, Iain B.
    Johnson, Mark
    PROCEEDINGS OF THE 2016 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM (PLANS), 2016, : 577 - 583
  • [9] Constrained fits with non-Gaussian distributions
    Fruehwirth, R.
    Cencic, O.
    17TH INTERNATIONAL WORKSHOP ON ADVANCED COMPUTING AND ANALYSIS TECHNIQUES IN PHYSICS RESEARCH (ACAT2016), 2016, 762
  • [10] STABLE NON-GAUSSIAN DISTRIBUTIONS IN SCIENTOMETRICS
    YABLONSKY, AI
    SCIENTOMETRICS, 1985, 7 (3-6) : 459 - 470