Search results
Results from the WOW.Com Content Network
The rate of reinforcement for fixed-ratio schedules is easy to calculate, as reinforcement rate is directly proportional to response rate and inversely proportional to ratio requirement (Killeen, 1994). The schedule feedback function is therefore: =.
The subscripts indicate the different stimulus contexts. Thus, Equation 2 states that relative resistance to change is a power function of the relative rate of reinforcement across stimulus contexts, with the a parameter indicating sensitivity to relative reinforcement rate. Consistent with behavioral momentum theory, resistance to disruption ...
In behaviorism, rate of reinforcement is number of reinforcements per time, usually per minute. Symbol of this rate is usually Rf. Its first major exponent was B.F. Skinner (1939). It is used in the Matching Law. Rf = # of reinforcements/unit of time = S R+ /t
The corpulence index yields valid results even for very short and very tall persons, [7] which is a problem with BMI — for example, an ideal body weight for a person 152.4 cm tall (48 kg) will render BMI of 20.7 and CI of 13.6, while for a person 200 cm tall (99 kg), the BMI will be 24.8, very close to the "overweight" threshold of 25, while ...
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...
In data mining and association rule learning, lift is a measure of the performance of a targeting model (association rule) at predicting or classifying cases as having an enhanced response (with respect to the population as a whole), measured against a random choice targeting model.
The weight is given by the likelihood ratio, that is, the Radon–Nikodym derivative of the true underlying distribution with respect to the biased simulation distribution. The fundamental issue in implementing importance sampling simulation is the choice of the biased distribution which encourages the important regions of the input variables.
As expected in an ideally distributed population of goldfish of different competitive abilities, the intake rate of each competitive weight did not differ between the sites. [ 8 ] Additionally, foraging behavior in coho salmon does not uphold ideal free distribution predicted by the equal competitors model, but does uphold ideal free ...