Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Functional Data Analysis (2)
- Proteomics (2)
- Apery’s constant. (1)
- Bernoulli number. (1)
- Bernoulli polynomial (1)
-
- Completely multiplicative function (1)
- Dirichlet series (1)
- Euler polynomial (1)
- Euler’s formula (1)
- Mobius function and Mobius inversion (1)
- Multiplicative function (1)
- Multivariate Riordan array pair (1)
- Multivariate Sheffer-type differential operators (1)
- Multivariate Sheffer-type polynomials (1)
- Multivariate exponential polynomials. (1)
- Multivariate formal power series (1)
- Multivariate weighted Stirling numbers (1)
- M¨obius inversion (1)
- Number Theory (1)
- Riemann Zeta function (1)
- Riemann zeta function (1)
- Selberg multiplicative functions. (1)
- Statistical Models (1)
Articles 1 - 11 of 11
Full-Text Articles in Applied Mathematics
Prepms: Tof Ms Data Graphical Preprocessing Tool, Yuliya V. Karpievitch, Elizabeth G. Hill, Adam J. Smolka, Jeffrey S. Morris, Kevin R. Coombes, Keith A. Baggerly, Jonas S. Almeida
Prepms: Tof Ms Data Graphical Preprocessing Tool, Yuliya V. Karpievitch, Elizabeth G. Hill, Adam J. Smolka, Jeffrey S. Morris, Kevin R. Coombes, Keith A. Baggerly, Jonas S. Almeida
Jeffrey S. Morris
We introduce a simple-to-use graphical tool that enables researchers to easily prepare time-of-flight mass spectrometry data for analysis. For ease of use, the graphical executable provides default parameter settings experimentally determined to work well in most situations. These values can be changed by the user if desired. PrepMS is a stand-alone application made freely available (open source), and is under the General Public License (GPL). Its graphical user interface, default parameter settings, and display plots allow PrepMS to be used effectively for data preprocessing, peak detection, and visual data quality assessment.
A Mathematical Regression Of The U.S. Gross Private Domestic Investment 1959-2001, Byron E. Bell
A Mathematical Regression Of The U.S. Gross Private Domestic Investment 1959-2001, Byron E. Bell
Byron E. Bell
SUMMARY OF PROJECT What did I do? A study of the role the U.S. stock markets and money markets have possibly played in the Gross Private Domestic Investment (GPDI) of the United States from the year 1959 to the year 2001 and I created a Multiple Linear Regression Model (MLRM).
Wavelet-Based Functional Mixed Models, Jeffrey S. Morris, Raymond J. Carroll
Wavelet-Based Functional Mixed Models, Jeffrey S. Morris, Raymond J. Carroll
Jeffrey S. Morris
Increasingly, Increasingly, scientific studies yield functional data, in which the ideal units of observation are curves and the observed data consist of sets of curves that are sampled on a fine grid. We present new methodology that generalizes the linear mixed model to the functional mixed model framework, with model fitting done by using a Bayesian wavelet-based approach. This method is flexible, allowing functions of arbitrary formand the full range of fixed effects structures and between-curve covariance structures that are available in the mixed model framework. It yields nonparametric estimates of the fixed and random-effects functions as well as the …
Analysis Of Mass Spectrometry Data Using Bayesian Wavelet-Based Functional Mixed Models, Jeffrey S. Morris, Philip J. Brown, Keith A. Baggerly, Kevin R. Coombes
Analysis Of Mass Spectrometry Data Using Bayesian Wavelet-Based Functional Mixed Models, Jeffrey S. Morris, Philip J. Brown, Keith A. Baggerly, Kevin R. Coombes
Jeffrey S. Morris
In this chapter, we demonstrate how to analyze MALDI-TOF/SELDITOF mass spectrometry data using the wavelet-based functional mixed model introduced by Morris and Carroll (2006), which generalizes the linear mixed models to the case of functional data. This approach models each spectrum as a function, and is very general, accommodating a broad class of experimental designs and allowing one to model nonparametric functional effects for various factors, which can be conditions of interest (e.g. cancer/normal) or experimental factors (blocking factors). Inference on these functional effects allows us to identify protein peaks related to various outcomes of interest, including dichotomous outcomes, categorical …
Fun With Fractals, Borbala Mazzag
Multivariate Expansion Associated With Sheffer-Type Polynomials And Operators, Tian-Xiao He, Leetsch Hsu, Peter Shiue
Multivariate Expansion Associated With Sheffer-Type Polynomials And Operators, Tian-Xiao He, Leetsch Hsu, Peter Shiue
Tian-Xiao He
With the aid of multivariate Sheffer-type polynomials and differential operators, this paper provides two kinds of general expansion formulas, called respectively the first expansion formula and the second expansion formula, that yield a constructive solution to the problem of the expansion of A(ˆt)f([g(t)) (a composition of any given formal power series) and the expansion of the multivariate entire functions in terms of multivariate Sheffer-type polynomials, which may be considered an application of the first expansion formula and the Sheffer-type operators. The results are applicable to combinatorics and special function theory.
On The Convergence Of The Summation Formulas Constructed By Using A Symbolic Operator Approach, Tian-Xiao He, Leetsch C. Hsu, Peter J.-S. Shiue
On The Convergence Of The Summation Formulas Constructed By Using A Symbolic Operator Approach, Tian-Xiao He, Leetsch C. Hsu, Peter J.-S. Shiue
Tian-Xiao He
This paper deals with the convergence of the summation of power series of the form Σa ≤ k ≤ bf(k)xk, where 0 ≤ a ≤ b < ∞, and {f(k)} is a given sequence of numbers with k ∈ [a, b) or f(t) a differentiable function defined on [a, b). Here, the summation is found by using the symbolic operator approach shown in [1]. We will give a different type of the remainder of the summation formulas. The convergence of the corresponding power series will be determined consequently. Several examples such as the generalized Euler's transformation series will also be given. In addition, we will compare the convergence of the given series transforms.
Numerical Approximation To Ζ(2n+1), Tian-Xiao He, Michael J. Dancs
Numerical Approximation To Ζ(2n+1), Tian-Xiao He, Michael J. Dancs
Tian-Xiao He
In this short paper, we establish a family of rapidly converging series expansions ζ(2n +1) by discretizing an integral representation given by Cvijovic and Klinowski [3] in Integral representations of the Riemann zeta function for odd-integer arguments, J. Comput. Appl. Math. 142 (2002) 435–439. The proofs are elementary, using basic properties of the Bernoulli polynomials.
On The Generalized Möbius Inversion Formulas, Tian-Xiao He, Peter J. S. Shiue3, Leetsch C. Hsu
On The Generalized Möbius Inversion Formulas, Tian-Xiao He, Peter J. S. Shiue3, Leetsch C. Hsu
Tian-Xiao He
We provide a wide class of M¨obius inversion formulas in terms of the generalized M¨obius functions and its application to the setting of the Selberg multiplicative functions.
An Euler-Type Formula For Ζ(2k +1), Tian-Xiao He, Michael J. Dancs
An Euler-Type Formula For Ζ(2k +1), Tian-Xiao He, Michael J. Dancs
Tian-Xiao He
In this short paper, we give several new formulas for ζ(n) when n is an odd positive integer. The method is based on a recent proof, due to H. Tsumura, of Euler’s classical result for even n. Our results illuminate the similarities between the even and odd cases, and may give some insight into why the odd case is much more difficult.
An Euler-Type Formula For Zeta (2k+1), Tian-Xiao He
An Euler-Type Formula For Zeta (2k+1), Tian-Xiao He
Tian-Xiao He
No abstract provided.