- In
probability theory and statistics,
covariance is a
measure of the
joint variability of two
random variables. The sign of the covariance, therefore,...
-
Harold Kelley's
covariation model (1967, 1971, 1972, 1973) is an
attribution theory in
which people make
causal inferences to
explain why
other people...
- this is in
particular the case for
Brownian motion. More generally, the
covariation (or cross-variance) of two
processes X {\displaystyle X} and Y {\displaystyle...
- Kelley,
individuals make
attributions by
utilizing the
covariation principle. The
covariation principle claims that
people attribute behavior to the factors...
-
contingent upon causes;
cause and
effect have a
probable relationship. The
covariation (regularity) model, a type of
dependency model,
suggests that humans...
-
denotes the
optional quadratic covariation of the
continuous parts of X and Y,
which is the
optional quadratic covariation minus the
jumps of the processes...
-
explained by a
covariation bias. In an
experiment (Schienle et al. 1996) 22
believers and 20
skeptics were
asked to
judge the
covariation between transmitted...
-
transformation of
random variable X {\displaystyle \mathbf {X} } with
covariation matrix Σ X = c o v ( X ) {\displaystyle \mathbf {\Sigma _{X}} =\mathrm...
-
stochastic integral commutes with the
operation of
taking quadratic covariations. If X and Y are
semimartingales then any X-integrable
process will also...
-
initio with the
sequence only (usually by
machine learning, ****isted by
covariation). The
structures for
individual domains are
docked together in a process...
