Moment (mathematics) | Generating functions | Factorial and binomial topics

Factorial moment generating function

In probability theory and statistics, the factorial moment generating function (FMGF) of the probability distribution of a real-valued random variable X is defined as for all complex numbers t for which this expected value exists. This is the case at least for all t on the unit circle , see characteristic function. If X is a discrete random variable taking values only in the set {0,1, ...} of non-negative integers, then is also called probability-generating function (PGF) of X and is well-defined at least for all t on the closed unit disk . The factorial moment generating function generates the factorial moments of the probability distribution.Provided exists in a neighbourhood of t = 1, the nth factorial moment is given by where the Pochhammer symbol (x)n is the falling factorial (Many mathematicians, especially in the field of special functions, use the same notation to represent the rising factorial.) (Wikipedia).

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Defining a Factorial Function

Defining a function in Python

From playlist Computer Science

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Factorial of a Matrix!

Today, we define the factorial of a matrix using the pi function and power series.

From playlist Linear Algebra

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Recursive Factorial Function

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From playlist Computer Science

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extending the factorial (the Gamma function & the Pi function)

The usual definition for a factorial only works for positive whole numbers, but how can we take the factorial of any number? Here we will discuss the Pi Function which is defined in terms of an improper integral and it is also the cousin of the Gamma function. I also show the properties of

From playlist Factorial Family, #MathForFun

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Determine Generating Functions of Sequences from Known Generating Functions (Part 2)

This video explains how to determine generating functions of sequences from known generating functions. mathispower4u.com

From playlist Additional Topics: Generating Functions and Intro to Number Theory (Discrete Math)

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Factoring a binomial using distributive property

👉Learn how to factor quadratics using the difference of two squares method. When a quadratic contains two terms where each of the terms can be expressed as the square of a number and the sign between the two terms is the minus sign, then the quadratic can be factored easily using the diffe

From playlist Factor Quadratic Expressions | Difference of Two Squares

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Simplifying a factorial divided by another factorial

👉 Learn all about factorials. Factorials are the multiplication of a number in descending integer values back to one. Factorials are used often in sequences, series, permutations, and combinations. Factorial quotient expressions are simplified by canceling out common integer products or

From playlist Sequences

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Master Solving quadratic equations by factoring when a is not 1

Subscribe! http://www.freemathvideos.com Welcome, ladies and gentlemen. So what I'd like to do is show you how to solve quadratic equations by using factoring when a is not equal to 1. So basically, it's going to be very similar to what we have done when a was equal to 1, but there's a lit

From playlist Quadratic Functions #Master

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Karol Penson - Hausdorff moment problems for combinatorial numbers: heuristics via Meijer (...)

We report on further investigations of combinatorial sequences in form of integral ratios of factorials. We conceive these integers as Hausdorff power moments for weights W (x), concentrated on the support x ∈ (0, R), and we solve this mo- ment problem by furnishing the exact expressions f

From playlist Combinatorics and Arithmetic for Physics: Special Days 2022

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What is factoring

👉Learn the basics of factoring quadratics by using different techniques. Some of the techniques used in factoring quadratics include: when the coefficient of the squared term is not 1. In that case, we first write the quadratic in standard form, next we multiply the coefficient of the squa

From playlist Factor Quadratic Expressions

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Probability and Random variables by VijayKumar Krishnamurthy

Winter School on Quantitative Systems Biology DATE: 04 December 2017 to 22 December 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru The International Centre for Theoretical Sciences (ICTS) and the Abdus Salam International Centre for Theoretical Physics (ICTP), are organizing a Wint

From playlist Winter School on Quantitative Systems Biology

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Jon Keating: Random matrices, integrability, and number theory - Lecture 4

Abstract: I will give an overview of connections between Random Matrix Theory and Number Theory, in particular connections with the theory of the Riemann zeta-function and zeta functions defined in function fields. I will then discuss recent developments in which integrability plays an imp

From playlist Analysis and its Applications

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Statistical Mechanics Lecture 3

(April 15, 20123) Leonard Susskind begins the derivation of the distribution of energy states that represents maximum entropy in a system at equilibrium. Originally presented in the Stanford Continuing Studies Program. Stanford University: http://www.stanford.edu/ Continuing Studies P

From playlist Course | Statistical Mechanics

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Roland Bauerschmidt - The Renormalisation Group - a Mathematical Perspective (2/4)

In physics, the renormalisation group provides a powerful point of view to understand random systems with strong correlations. Despite advances in a number of particular problems, in general its mathematical justification remains a holy grail. I will give an introduction to the main concep

From playlist Roland Bauerschmidt - The Renormalisation Group - a Mathematical Perspective

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Foundations - Seminar 11 - Gödel's incompleteness theorem Part 3

Billy Price and Will Troiani present a series of seminars on foundations of mathematics. In this seminar Will Troiani continues with the proof of Gödel's incompleteness theorem, discussing Gödel's beta function and the role of the Chinese Remainder theorem in the incompleteness theorem. Y

From playlist Foundations seminar

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Introduction to Probability and Statistics 131B. Lecture 01.

UCI Math 131B: Introduction to Probability and Statistics (Summer 2013) Lec 01. Introduction to Probability and Statistics View the complete course: http://ocw.uci.edu/courses/math_131b_introduction_to_probability_and_statistics.html Instructor: Michael C. Cranston, Ph.D. License: Creativ

From playlist Introduction to Probability and Statistics 131B

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Tides in binary star systems (Lecture - 01) by Tanja Hinderer

Summer School on Gravitational-Wave Astronomy DATE: 17 July 2017 to 28 July 2017 VENUE: Madhava Lecture Hall, ICTS Bangalore This school is a part of the annual ICTS summer schools in gravitational wave astronomy. This year’s school will focus on the physics and astrophysics of compact

From playlist Summer School on Gravitational-Wave Astronomy - 2017

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Non-equilibrium statistical physics: Introductory examples (Lecture - 02) by Sidney Redner

Bangalore School on Statistical Physics - VIII DATE: 28 June 2017 to 14 July 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru This advanced level school is the eighth in the series. This is a pedagogical school, aimed at bridging the gap between masters-level courses and topics in s

From playlist Bangalore School on Statistical Physics - VIII

Related pages

Moment (mathematics) | Factorial moment | Statistics | Exponential function | Unit disk | Probability-generating function | Poisson distribution | Neighbourhood (mathematics) | Cumulant-generating function | Unit circle | Integer | Real number | Probability distribution | Random variable | Expected value | Complex number | Moment-generating function | Probability theory | Characteristic function (probability theory) | Closed set