Posterior chain information

The posterior chain is a group of muscles on the posterior of the body. Examples of these muscles include the hamstrings, the gluteus maximus, erector...

The anterior chain, which comprises the antagonists of the posterior chain, refers to the group of skeletal muscles that lies on the front of the human...

Strengthening the quadriceps, glutes, hamstrings, and other muscles of the posterior chain. In addition to building strength and muscle mass, the sumo deadlift...

mechanics, strengthening the hamstrings and glutes, and enhancing overall posterior chain development. They are often used in strength training and sports performance...

kettlebell swing) is a basic ballistic exercise used to train the posterior chain in a manner similar to broad jumping. It involves moving the bell in...

hyper-extensions on a Roman chair or the inflatable ball will strengthen all the posterior chain and will treat hyperlordosis. So too will stiff-legged deadlifts and...

Bayesian statistics, Markov chain Monte Carlo methods are typically used to calculate moments and credible intervals of posterior probability distributions...

methods, allowing a wide range of posterior distributions to be simulated and their parameters found numerically. Markov chains are used in finance and economics...

The posterior probability is a type of conditional probability that results from updating the prior probability with information summarized by the likelihood...

conventional kettlebell swing) is a basic ballistic used to train the posterior chain in a manner similar to broad jumping. The kettlebell is swung from...

mode of the posterior and is often computed in Bayesian statistics using mathematical optimization methods, remains the same. The posterior can be approximated...

In Bayesian statistics, the posterior predictive distribution is the distribution of possible unobserved values conditional on the observed values. Given...

In statistics, Gibbs sampling or a Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for sampling from a specified multivariate probability...

estimate is an estimate of an unknown quantity, that equals the mode of the posterior distribution. The MAP can be used to obtain a point estimate of an unobserved...

process of computing the posterior distribution of variables given evidence is called probabilistic inference. The posterior gives a universal sufficient...

strength exercise because it dynamically involves both the anterior and posterior chains in a harmonious fashion. There are numerous variations of the Hindu...

credible interval. Credible intervals are typically used to characterize posterior probability distributions or predictive probability distributions. The...

for that it would result in a tractable posterior of the same family. The widespread availability of Markov chain Monte Carlo methods, however, has made...

probabilist specifies a prior probability. This, in turn, is then updated to a posterior probability in the light of new, relevant data (evidence). The Bayesian...

of the 4th thoracic vertebra posteriorly; laterally by the pleurae; anteriorly by the manubrium of the sternum; posteriorly by the first four thoracic vertebral...

multiple levels (hierarchical form) that estimates the parameters of the posterior distribution using the Bayesian method. The sub-models combine to form...

curves posteriorly. Its body outline resembles that of the northern pike (E. lucius). Unlike northern pike, however, the opercles and cheeks of chain pickerel...

approximating a posterior probability), variational Bayes is an alternative to Monte Carlo sampling methods—particularly, Markov chain Monte Carlo methods...

dorsal root ganglia. They pass through Rexed laminae layers I-VI of the posterior grey column (dorsal horn) to form synapses with second order or secondary...

Modern Markov chain Monte Carlo methods have boosted the importance of Bayes' theorem including cases with improper priors. The posterior predictive distribution...

(MLE). But since the posterior is a gamma distribution, the MLE of the marginal turns out to be just the mean of the posterior, which is the point estimate...

minimizes the posterior expected value of a loss function (i.e., the posterior expected loss). Equivalently, it maximizes the posterior expectation of...