Calibrating magnification bias for the EG statistic to test general relativity
نویسندگان
چکیده
منابع مشابه
General Saddlepoint Approximations: Application to the Anderson-Darling Test Statistic
We consider the relative merits of various saddlepoint approximations for the c.d.f. of a statistic with a possibly non-normal limit distribution. In addition to the usual Lugannani-Rice approximation we also consider approximations based on higher-order expansions, including the case where the base distribution for the approximation is taken to be non-normal. This extends earlier work by Wood ...
متن کاملA Cosmological Test for General Relativity
The latest results in cosmography as well as the latest observations of the cosmic microwave background (CMB) and of supernovae have reinforced the emergence of a canonical paradigm for cosmology. Most of the cosmological parameters constituting this concordance model are now known up to five per cent of relative accuracy. We can rely on these accurate values of the parameters if the fundamenta...
متن کاملIntroduction to Tensor Calculus for General Relativity
There are three essential ideas underlying general relativity (GR). The first is that spacetime may be described as a curved, four-dimensional mathematical structure called a pseudo-Riemannian manifold. In brief, time and space together comprise a curved fourdimensional non-Euclidean geometry. Consequently, the practitioner of GR must be familiar with the fundamental geometrical properties of c...
متن کاملOn the Bias of the Portmanteau Statistic
The portmanteau statistic is based on the first m residual autocorrelations, and is used for diagnostic checks on the adequacy of a fitting model. In this paper, we propose a modified portmanteau statistic with a correction factor that allows for the use of small values of m and eliminates the positively biased random variable for the chi-squared approximation. For this modification we take a d...
متن کاملEstimation Sampling Sampling Estimation Sampling Test Statistic Test Statistic
In this paper, we introduce a Goodness-of-Fit test for the Multivariate Exponential Power (MEP) distribution, a multivariate extension of the Generalized Gaussian, which has recently gained considerable interest as a model for wavelet coefficients in the context of color image retrieval and spread-spectrum watermarking. We present a size and power study of this test and show Goodness-of-Fit res...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Monthly Notices of the Royal Astronomical Society
سال: 2018
ISSN: 0035-8711,1365-2966
DOI: 10.1093/mnras/sty2353