This thesis discusses the design and evaluation of an instrument that can estimate the probability density distributions of bandlimited, aperiodic electrical phenomena. This estimator can obtain the probability density estimates of signals that are contained within the frequency range of 100 cps. to 20 kcs. However, the basic design logic...
A probability model has been developed for the survival of
irradiated bacteria with respect to the dose of radiation. This model
is applicable to those bacterial taxa to which the target theory applies.
Three estimation procedures are given for the purpose of
obtaining estimates of the probability model's parameters. These...
The exponential family of probability distributions is obtained
from σ-finite measures on the real line. We choose the parameter
space to be one-dimensional and the exponent to be linear. Relationships
between the measure, its spectrum, and the parameter space
are examined, moments of the exponential family are studied, and
the...
Before we apply the laws of probability to hiring practices, a
foundation of basic probability theory will be presented. In this
presentation a number of theorems related to probability will be
proven. These theorems are not necessarily applicable to the problem
which follows; however, they are basic to probability theory...
This thesis gives a procedure for generalizing the concept of
conditional probability applied to the case of the bivariate probability
density function.
The conditional probability density function is desired where the two variables vary according to some prescribed path Φ which lies in the plane of the two variables. Instead...
This study was concerned with the estimation of transition probabilities
in a finite state Markov-type student flow model. Goals
setting for this study were three in number: (1) Study of the methods
which will provide conclusions that (a) the transition probabilities
are stationary or nonstationary and (b) the process is...
This thesis is concerned with the problem of developing a
method to categorize probability models by their outlier properties.
There have been two such categorization methods proposed in the
literature. Neyman and Scott (1971) classify an entire family of
distributions into the outlier properties outlier-prone completely
(OPC) and outlier resistant....
There are three families of exact methods used for probabilistic inference in
belief nets. It is necessary to compare them and analyze the advantages and
the disadvantages of each algorithm, and know the time cost of making
inferences in a given belief network. This paper discusses the factors that
influence...