scholarly journals Intuitive Joint Priors for Variance Parameters

2020 ◽  
Vol 15 (4) ◽  
pp. 1109-1137 ◽  
Author(s):  
Geir-Arne Fuglstad ◽  
Ingeborg Gullikstad Hem ◽  
Alexander Knight ◽  
Håvard Rue ◽  
Andrea Riebler
Keyword(s):  
Variance Parameters

Translocation Relative to Range

Methodology ◽  
2008 ◽  
Vol 4 (3) ◽  
pp. 132-138 ◽  
Author(s):  
Michael Höfler
Keyword(s):  
Risk Difference ◽  
Binary Outcomes ◽  
Number Needed To Treat ◽  
Likert Scales ◽  
Psychological Science ◽  
The Absolute ◽  
The Difference ◽  
Variance Parameters ◽  
Standardized Index ◽  
Maximum Possible Magnitude

A standardized index for effect intensity, the translocation relative to range (TRR), is discussed. TRR is defined as the difference between the expectations of an outcome under two conditions (the absolute increment) divided by the maximum possible amount for that difference. TRR measures the shift caused by a factor relative to the maximum possible magnitude of that shift. For binary outcomes, TRR simply equals the risk difference, also known as the inverse number needed to treat. TRR ranges from –1 to 1 but is – unlike a correlation coefficient – a measure for effect intensity, because it does not rely on variance parameters in a certain population as do effect size measures (e.g., correlations, Cohen’s d). However, the use of TRR is restricted on outcomes with fixed and meaningful endpoints given, for instance, for meaningful psychological questionnaires or Likert scales. The use of TRR vs. Cohen’s d is illustrated with three examples from Psychological Science 2006 (issues 5 through 8). It is argued that, whenever TRR applies, it should complement Cohen’s d to avoid the problems related to the latter. In any case, the absolute increment should complement d.

scholarly journals GENETIC PARAMETERS FOR GROWTH TRAITS OF SANTA INES SHEEP USING GIBBS SAMPLING

2015 ◽  
Vol 28 (4) ◽  
pp. 211-216 ◽  
Author(s):  
LEANDRO TEIXEIRA BARBOSA ◽  
GLEICIANNY DE BRITO SANTOS ◽  
EVANDRO NEVES MUNIZ ◽  
HYMERSON COSTA AZEVEDO ◽  
JAILSON LARA FAGUNDES
Keyword(s):  
Gibbs Sampling ◽  
Genetic Parameters ◽  
Mixed Model ◽  
Growth Traits ◽  
Meat Production ◽  
Gibbs Sampling Algorithm ◽  
Santa Inês ◽  
Variance Parameters ◽  
Additive Genetic Effects ◽  
Maternal Heritability

ABSTRACT: This study sought to estimate (co)variance and genetic parameters for birth weight (BWT) and weaning weight (WWT) in Santa Ines sheep. A total of 2,111 records were obtained from EMBRAPA/CPATC experimental herds, dating from the years 1998 to 2008. (Co)variance parameters were obtained through a two-trait analysis with the Gibbs sampling algorithm using the MTGSAM program. The mixed model included the environmental effects of sex, contemporary group and type of birth, in addition to residual, direct and maternal additive effects. Mean estimates of direct heritability for BWT and WWT were 0.25 and 0.09, respectively. Mean estimates of maternal heritability were 0.34 for BWT and 0.24 for WWT. The genetic correlation between BWT and WWT was 0.14. The results suggest that breeding Santa Ines sheep for meat production must take into consideration direct and maternal additive genetic effects.

scholarly journals Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics

2022 ◽  
Vol 14 (2) ◽  
pp. 375
Author(s):  
Sina Voshtani ◽  
Richard Ménard ◽  
Thomas W. Walker ◽  
Amir Hakami
Keyword(s):  
Kalman Filter ◽  
Cross Validation ◽  
Error Variance ◽  
Error Statistics ◽  
Optimal Error ◽  
Meaningful Improvement ◽  
Aircraft Observations ◽  
Variance Parameters ◽  
Analysis Error ◽  
Or Modelling

We applied the parametric variance Kalman filter (PvKF) data assimilation designed in Part I of this two-part paper to GOSAT methane observations with the hemispheric version of CMAQ to obtain the methane field (i.e., optimized analysis) with its error variance. Although the Kalman filter computes error covariances, the optimality depends on how these covariances reflect the true error statistics. To achieve more accurate representation, we optimize the global variance parameters, including correlation length scales and observation errors, based on a cross-validation cost function. The model and the initial error are then estimated according to the normalized variance matching diagnostic, also to maintain a stable analysis error variance over time. The assimilation results in April 2010 are validated against independent surface and aircraft observations. The statistics of the comparison of the model and analysis show a meaningful improvement against all four types of available observations. Having the advantage of continuous assimilation, we showed that the analysis also aims at pursuing the temporal variation of independent measurements, as opposed to the model. Finally, the performance of the PvKF assimilation in capturing the spatial structure of bias and uncertainty reduction across the Northern Hemisphere is examined, indicating the capability of analysis in addressing those biases originated, whether from inaccurate emissions or modelling error.

Asymptotic variance parameters for the boundary local times of reflected Brownian motion on a compact interval

1992 ◽  
Vol 29 (04) ◽  
pp. 996-1002 ◽  
Author(s):  
R. J. Williams
Keyword(s):  
Brownian Motion ◽  
Asymptotic Variance ◽  
Hitting Time ◽  
Local Times ◽  
Compact Interval ◽  
Reflected Brownian Motion ◽  
Direct Derivation ◽  
One Dimensional ◽  
Brownian Motion With Drift ◽  
Variance Parameters

A direct derivation is given of a formula for the normalized asymptotic variance parameters of the boundary local times of reflected Brownian motion (with drift) on a compact interval. This formula was previously obtained by Berger and Whitt using an M/M/1/C queue approximation to the reflected Brownian motion. The bivariate Laplace transform of the hitting time of a level and the boundary local time up to that hitting time, for a one-dimensional reflected Brownian motion with drift, is obtained as part of the derivation.

Finite-time optimal control of a process leaving an interval

1996 ◽  
Vol 33 (03) ◽  
pp. 714-728
Author(s):  
Douglas W. Mcbeth ◽  
Ananda P. N. Weerasinghe
Keyword(s):  
Optimal Control ◽  
Discrete Time ◽  
Finite Time ◽  
Simple Random Walk ◽  
Time Instant ◽  
Initial Position ◽  
Time Problem ◽  
Control Set ◽  
Playing Time ◽  
Variance Parameters

Consider the optimal control problem of leaving an interval (– a, a) in a limited playing time. In the discrete-time problem, a is a positive integer and the player's position is given by a simple random walk on the integers with initial position x. At each time instant, the player chooses a coin from a control set where the probability of returning heads depends on the current position and the remaining amount of playing time, and the player is betting a unit value on the toss of the coin: heads returning +1 and tails − 1. We discuss the optimal strategy for this discrete-time game. In the continuous-time problem the player chooses infinitesimal mean and infinitesimal variance parameters from a control set which may depend upon the player's position. The problem is to find optimal mean and variance parameters that maximize the probability of leaving the interval [— a, a] within a finite time T > 0.

Online Estimation of Allan Variance Parameters

2000 ◽  
Vol 23 (6) ◽  
pp. 980-987 ◽  
Author(s):  
Jason J. Ford ◽  
Michael E. Evans
Keyword(s):  
Allan Variance ◽  
Online Estimation ◽  
Variance Parameters
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