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Publications

Search Publications by

Hariharan K. Iyer (Fed)

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Displaying 1 - 25 of 25

Quantitative Evaluation of Footwear Evidence: Initial Workflow for an End-to-End System

November 23, 2021
Author(s)
Gautham Venkatasubramanian, Vighnesh Hegde, Steven Lund, Hariharan K. Iyer, Martin Herman
In the U.S., footwear examiners make decisions about the sources of crime scene shoe impressions using subjective criteria. This has raised questions about the accuracy, repeatability, reproducibility, and scientific validity of footwear examinations

Some Statistical Methods Applicable to Key Comparisons Studies

October 12, 2021
Author(s)
Hariharan K. Iyer, Chih-Ming Wang, Dominic F. Vecchia
Results of International Key Comparisons of National Measurement Standards provide the technical basis for the Mutual Recognition Arrangement formulated by Le Comite International des Poids et Mesures. With many key comparisons already completed and a

Towards Absolute Viability Measurements for Bacteria

September 12, 2021
Author(s)
Joy Dunkers, Hariharan K. Iyer, Brynna H. Jones, Charles Camp, Stephan J. Stranick, Nancy Lin
Quantifying viable, vegetative bacteria is a critical measurand in healthcare diagnostics, food safety, and antimicrobial development. Viability determination has traditionally relied on such techniques as plate counting, colorimetric or fluorescent

NIST Scientific Foundation Reviews

December 18, 2020
Author(s)
John M. Butler, Hariharan K. Iyer, Richard A. Press, Melissa Taylor, Peter Vallone, Sheila Willis
The National Institute of Standards and Technology (NIST) is a scientific research agency that works to advance measurement science, standards, and technology and that has been working to strengthen forensic science methods for almost a century. In recent

Understanding the characteristics of sequence-based single-source DNA profiles

November 9, 2019
Author(s)
Sarah Riman, Hariharan K. Iyer, Lisa A. Borsuk, Peter M. Vallone
The sequencing of STR markers provides additional information present in the underlying sequence variation that is typically masked by traditional fragment-based genotyping. However, the interpretation of STR profiles generated by targeted sequencing

Combinatorial Cassettes for Higher-Throughput Screening of Osteogenesis

October 4, 2018
Author(s)
Carl G. Simon Jr., Subhadip Bodhak, Hariharan K. Iyer, Luis Fernandez de Castro Diaz, Pam Robey, Azusa Maeda, Sergei Kuznetsov
Animal models are the most biologically relevant method for measuring the osteogenic capability of bone graft formulations. However, animal experiments are slow, tedious and the results can be highly variable, even when conducted within the same lab. In

Likelihood Ratio as Weight of Forensic Evidence: A Closer Look

October 12, 2017
Author(s)
Hariharan K. Iyer, Steven P. Lund
The forensic science community has increasingly sought quantitative methods for conveying the weight of evidence. Experts from many forensic laboratories summarize their fndings in terms of a likelihood ratio. Several proponents of this approach have

SVClassify: a method to use multiple datasets to classify candidate structural variants into true positives and false positives

January 16, 2016
Author(s)
Justin M. Zook, Hemang M. Parikh, Desu Chen, Hariharan K. Iyer, Marc L. Salit, Wolfgang Losert
The human genome contains variants ranging in size from small single nucleotide polymorphisms (SNPs) to large structural variants (SVs). While high-quality benchmark small variant calls have recently been developed by the Genome in a Bottle Consortium, no

Pivotal Methods in the Propagation of Distributions

April 24, 2012
Author(s)
Chih-Ming Wang, Jan Hannig, Hariharan K. Iyer
We propose a method for assigning a probability distribution to an input quantity. The distribution is used in the Monte Carlo method for uncertainty evaluation. The proposed method provides an alternative to other methods, such as the principle of maximum

Fiducial Prediction Intervals

February 18, 2012
Author(s)
Chih-Ming Wang, Jan Hannig, Hariharan K. Iyer
This paper presents an approach for constructing prediction intervals for any given distribution. The approach is based on the principle of fiducial inference. We use several examples, including the normal, binomial, gamma, and Weibull distributions, to

On Non-Linear Estimation of a Measurand

November 7, 2011
Author(s)
Chih-Ming Wang, Hariharan K. Iyer
We consider an estimation problem described in the Guide to the Expression of Uncertainty in Measurement (GUM). The problem is concerned with estimating a measurand that is a non-linear function of input quantities. The GUM describes two methods for

On Multiple-Method Studies

October 4, 2010
Author(s)
Chih-Ming Wang, Hariharan K. Iyer
In this paper we review statistical models that describe measurements from a multiple-method study such as in the development of a reference material. We also review requirements for the so-called GUM compliance as this appears to be an important criterion

On interchangeability of two laboratories

June 18, 2010
Author(s)
Chih-Ming Wang, Hariharan K. Iyer
This paper proposes a measure for assessing the degree of equivalence between the two laboratories in a key comparison. The measure is called asymmetric degree of interchangeability. It is asymmetric since, based on this measure, a laboratory may be

Fiducial Intervals for the Magnitude of a Complex-Valued Quantity

December 19, 2008
Author(s)
Chih-Ming Wang, Hariharan K. Iyer
This paper discusses a fiducial approach for constructing uncertainty intervals for the distance between k normal means and the origin. When k=2 this distance is equivalent to the magnitude of a complex-valued quantity. Uncertainty intervals for the

Fiducial approach for assessing agreement between two instruments

July 9, 2008
Author(s)
Chih-Ming Wang, Hariharan K. Iyer
This paper presents an approach for making inferences about the intercept and the slope of a linear regression model with both variables subject to measurement errors. The approach is based on the principle of fiducial inference. A procedure is presented

Uncertainty Analysis for Vector Measurands Using Fiducial Inference

January 1, 2006
Author(s)
Chih-Ming Wang, Hariharan K. Iyer
This paper presents a method for constructing uncertainty regions for a vector measurand in the presence of both type-A and type-B errors. The method is based on the principle of fiducial inference and generally requires a Monte Carlo approach for

Propagation of Uncertainties in Measurements Using Structural Inference

March 21, 2005
Author(s)
Hariharan K. Iyer, Chih-Ming Wang
The ISO Guide to the Expression of Uncertainty in Measurement (GUM) recommends the use of a first-order Taylor series expansion for propagating errors and uncertainties. The GUM also permits the use of other analytical or numerical methods when the

On Higher Order Corrections for Propagating Uncertainties

January 1, 2005
Author(s)
Chih-Ming Wang, Hariharan K. Iyer
The ISO Guide to the Expression of Uncertainty in Measurement (GUM) recommends the use of a first-order Taylor series expansion for propagating errors and uncertainties. The GUM also suggests the use of a second-order Taylor series approximation for

Propagation of uncertainties in measurements using generalized influence

January 1, 2005
Author(s)
Hariharan K. Iyer, Chih-Ming Wang
The ISO Guide to the Expression of Uncertainty in Measurement (GUM) recommends the use of a first- order Taylor series expansion for propagating errors and uncertainties. The GUM also permits the use of "other analytical or numerical methods" when the

Models and Confidence Intervals for True Values in Interlaboratory Trials

December 6, 2004
Author(s)
Hariharan K. Iyer, Chih-Ming Wang, T Mathew
We consider the one-way random effects model with unequal sample sizes and heterogeneous variances. Using the method of generalized confidence intervals, we develop a new confidence interval procedure for the mean. Additionally, we investigate two