Some experience with core math concepts such as difference equations or probability density functions is assumed, but review is included.
What does PDF stand for?
PDF stands for Probability Density Function
This definition appears very frequently and is found in the following Acronym Finder categories:
- Science, medicine, engineering, etc.
See other definitions of PDF
We have 1309 other meanings of PDF in our Acronym Attic
- Precision Direction Finding
- Premier Diesel Fuel (low sulfur diesel)
- Pretrial Detention Facility (various locations)
- Pretty Damn Funky
- Pretty Damn Funny
- Pretty Darn Fast
- Primary Direction of Fire
- Principal Direction of Fire
- Printer Definition File
- Printer Description File (File Name Extension)
- Probability Distribution Function
- Processor Defined Function
- Procurement Data File
- Product Development & Fulfillment company
- Professional Development Foundation (UK)
- Professional Development Fund (various organizations)
- Proficiency Diploma in French (Nigeria)
- Program Data File
- Program Data Form
- Program Development Facility
Samples in periodicals archive:
1) Dealing with the anomalous values of the Eaton index vector properly, then substituting the Eaton index into the Eaton formula for Monte Carlo simulation, finally the formation pore pressure matrix would be determined by statistically analyzing the results of Monte Carlo simulation; (2) Making statistical analysis directly of the Eaton index vector, then calculating the probability density function, and the distribution function of the formation pore pressure will be directly calculated by the union probability calculation method.
2] is given by: [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (1) where, pf) is the probability density function off.
Earlier it was shown (Krylovas, Kosareva 2008a, b) how segments of linear functions could be used as an item characteristic function and also as a probability density function of the population knowledge level.
The probability density function f([alpha]) obtained according to definition is given by [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (11) where [[alpha].
[lambda]]([lambda]), and then weighting them by the conditional probability density function [P.
3) According to the assumptions of the model, definition of probability density function, convolution and using Jacobian transformation the probability density function of [Y.
Let X be a random variable having the probability density function f: [a, b] [right arrow] R and there exist the constants M, m such that 0 [less than or equal to] m [less than or equal to] f(t) [less than or equal to] M [less than or equal to] 1 a.