Loughborough University Research Publications
Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Research Publications


Publications for Mohammad Salehi

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Journal Articles

Barkhudaryan, R, Gomes, DA, Shahgholian, H, Salehi, M (2022) System of variational inequalities with interconnected obstacles, Applicable Analysis, 101(2), pp.605-628, ISSN: 0003-6811. DOI: 10.1080/00036811.2020.1757076.

Salehi, M and Smith, DR (2021) Adaptive two-stage inverse sampling design to estimate density, abundance, and occupancy of rare and clustered populations, PLOS ONE, 16(8), pp.e0255256-e0255256, DOI: 10.1371/journal.pone.0255256.

Panahbehagh, B, Bruggemann, R, Salehi, M (2021) Sampling of Multiple Variables Based on Partially Ordered Set Theory, Journal of the Iranian Statistical Society, 20(1), pp.307-331, ISSN: 1726-4057. DOI: 10.52547/jirss.20.1.307.

Salehi M, M and Seber, GAF (2021) A new estimator and approach for estimating the subpopulation parameters, Journal of Taibah University for Science, 15(1), pp.288-294, DOI: 10.1080/16583655.2021.1979735.

Al Fakih, B, Morei, A, Salehi M, M (2020) Students Impression About Using Mobile Phones in Classroom, International Journal of Emerging Technologies in Learning (iJET), 15(22), pp.230-230, DOI: 10.3991/ijet.v15i22.16219.

Arakelyan, A, Barkhudaryan, R, Shahgholian, H, Salehi, M (2019) Numerical Treatment to a Non-local Parabolic Free Boundary Problem Arising in Financial Bubbles, Bulletin of the Iranian Mathematical Society, 45(1), pp.59-73, ISSN: 1017-060X. DOI: 10.1007/s41980-018-0119-5.

Farhadi, A, Salehi, M, Erjaee, GH (2018) A New Version of Black–Scholes Equation Presented by Time-Fractional Derivative, Iranian Journal of Science and Technology, Transactions A: Science, 42(4), pp.2159-2166, ISSN: 1028-6276. DOI: 10.1007/s40995-017-0244-7.

Panahbehagh, B, Bruggemann, R, Parvardeh, A, Salehi, M, Sabzalian, MR (2018) An Unbalanced Ranked-Set Sampling Method to Get More Than One Sample from Each Set, Journal of Survey Statistics and Methodology, 6(3), pp.285-305, ISSN: 2325-0984. DOI: 10.1093/jssam/smx026.

Salehi, MM (2017) Erratum: Two‐stage complete allocation sampling, Environmetrics, 28(7), e2461, ISSN: 1180-4009. DOI: 10.1002/env.2461.

Salehi, MM and Seber, GAF (2017) Two‐stage complete allocation sampling, Environmetrics, 28(3), e2441, ISSN: 1180-4009. DOI: 10.1002/env.2441.

Farhadi, A, Erjaee, GH, Salehi, M (2017) Derivation of a new Merton’s optimal problem presented by fractional stochastic stock price and its applications, Computers & Mathematics with Applications, 73(9), pp.2066-2075, ISSN: 0898-1221. DOI: 10.1016/j.camwa.2017.02.031.

Abi, N, Moradi, M, Salehi, M, Brown, J, Al-Khayat, JA, Moltchanova, E (2017) Application of Balanced Acceptance Sampling to an Intertidal Survey, Journal of Landscape Ecology, 10(1), pp.96-107, DOI: 10.1515/jlecol-2017-0012.

Barkhudaryan, R, Juráš, M, Salehi, M (2016) Iterative scheme for an elliptic non-local free boundary problem, Applicable Analysis, 95(12), pp.2794-2806, ISSN: 0003-6811. DOI: 10.1080/00036811.2015.1113528.

Salehi, M, Moradi, M, Al Khayat, JA, Brown, J, Yousif, AEM (2015) Inverse Adaptive Cluster Sampling with Unequal Selection Probabilities: Case Studies on Crab Holes and Arsenic Pollution, Australian & New Zealand Journal of Statistics, 57(2), pp.189-201, ISSN: 1369-1473. DOI: 10.1111/anzs.12118.

El Hajj, MS, Kheir, N, Al Mulla, AM, Al-Badriyeh, D, Al Kaddour, A, Mahfoud, ZR, Salehi, M, Fanous, N (2015) Assessing the effectiveness of a pharmacist-delivered smoking cessation program in the State of Qatar: study protocol for a randomized controlled trial, Trials, 16(1), 65, DOI: 10.1186/s13063-015-0570-z.

Mohammadi, M, Salehi, M, Rao, JNK (2014) Bootstrap confidence intervals for adaptive cluster sampling design based on Horvitz–Thompson type estimators, Environmental and Ecological Statistics, 21(2), pp.351-371, ISSN: 1352-8505. DOI: 10.1007/s10651-013-0258-z.

Salehi, M, Panahbehagh, B, Parvardeh, A, Smith, DR, Lei, Y (2013) Regression-type estimators for adaptive two-stage sequential sampling, Environmental and Ecological Statistics, 20(4), pp.571-590, ISSN: 1352-8505. DOI: 10.1007/s10651-012-0235-y.

Parvardeh, A, Panahbehagh, B, Salehi M, M, Brown, J, Smith, DR (2013) Asymptotic properties of the sample mean in adaptive stratified sequential sampling with multiple selection criteria, Bulletin of the Iranian Mathematical Society, 39(3), pp.529-557, ISSN: 1018-6301.

Brown, JA, Salehi M, M, Moradi, M, Panahbehagh, B, Smith, DR (2013) Adaptive survey designs for sampling rare and clustered populations, Mathematics and Computers in Simulation, 93, pp.108-116, ISSN: 0378-4754. DOI: 10.1016/j.matcom.2012.09.008.

Mohammadi, M and M, MS (2012) Horvitz-thompson estimator of population mean under inverse sampling designs, Bulletin of the Iranian Mathematical Society, 38(2), pp.333-347, ISSN: 1018-6301.

Moradi, M, Salehi, M, Brown, JA, Karimi, N (2011) Regression estimator under inverse sampling to estimate arsenic contamination, Environmetrics, 22(7), pp.894-900, ISSN: 1180-4009. DOI: 10.1002/env.1116.

Fazileh, F, Ghorbani, M, Maghoul, Z, Mirza, B, Salehi, MA (2011) Investigating the effect of disorder on density of states of graphene nano-ribbons, Iranian Journal of Physics Research, 11(2), pp.167-179, ISSN: 1682-6957.

Gavanji, P, Salehi, M, Gore, SD, Khademi, H, Ayoubi, S, Taghipour, M (2011) Use of post-stratification in composite sampling for estimating mean, Environmental and Ecological Statistics, 18(3), pp.535-542, ISSN: 1352-8505. DOI: 10.1007/s10651-010-0150-z.

(2011) International Encyclopedia of Statistical Science, DOI: 10.1007/978-3-642-04898-2.

Salehi, M, Moradi, M, Brown, JA, Smith, D (2010) Efficient estimators for adaptive stratified sequential sampling, Journal of Statistical Computation and Simulation, 80(10), pp.1163-1179, ISSN: 0094-9655. DOI: 10.1080/00949650903005664.

Salehi, M and Brown, JA (2010) Complete allocation sampling: an efficient and easily implemented adaptive sampling design, Population Ecology, 52(3), pp.451-456, ISSN: 1438-3896. DOI: 10.1007/s10144-010-0196-7.

Moradi, M and Salehi, M (2010) An adaptive allocation sampling design for which the conventional stratified estimator is an appropriate estimator, Journal of Statistical Planning and Inference, 140(4), pp.1030-1037, ISSN: 0378-3758. DOI: 10.1016/j.jspi.2009.10.003.

Salehi, M, Mohammadi, M, Rao, JNK, Berger, YG (2010) Empirical likelihood confidence intervals for adaptive cluster sampling, Environmental and Ecological Statistics, 17(1), pp.111-123, ISSN: 1352-8505. DOI: 10.1007/s10651-008-0105-9.

Salehi, M, Levy, PS, Rao, J (2010) Two-phase sample size estimation with pre-assignedvariance under normality assumption, Iranian Journal of Science and Technology Transaction A Science, 34(4), pp.349-353, ISSN: 1028-6276.

Brown, JA, Salehi M, M, Moradi, M, Bell, G, Smith, DR (2008) An adaptive two‐stage sequential design for sampling rare and clustered populations, Population Ecology, 50(3), pp.239-245, ISSN: 1438-3896. DOI: 10.1007/s10144-008-0089-1.

Nematollahi, N, Salehi M, M, Saba, RA (2008) Two-Stage Cluster Sampling with Ranked Set Sampling in the Secondary Sampling Frame, Communications in Statistics - Theory and Methods, 37(15), pp.2404-2415, ISSN: 0361-0926. DOI: 10.1080/03610920801919684.

Salehi, M (2006) Adaptive Cluster Row and Column Elimination Sampling +(1) Design, Communications in Statistics: Theory and Methods, 35(2), pp.349-362, ISSN: 0361-0926. DOI: 10.1080/03610920500440040.

Salehi, MM, Levy, PS, Jamalzadeh, MA, Chang, K (2006) Adaptation of multiple logistic regression to a multiple inverse sampling design: application to the Isfahan healthy heart program, Statistics in Medicine, 25(1), pp.71-85, ISSN: 0277-6715. DOI: 10.1002/sim.2288.

Mohammad Salehi, M and Chang, K-C (2005) Multiple inverse sampling in post-stratification with subpopulation sizes unknown: a solution for quota sampling, Journal of Statistical Planning and Inference, 131(2), pp.379-392, ISSN: 0378-3758. DOI: 10.1016/j.jspi.2004.02.002.

Salehi, MM and Smith, DR (2005) Two-stage sequential sampling: A neighborhood-free adaptive sampling procedure, Journal of Agricultural, Biological, and Environmental Statistics, 10(1), pp.84-103, ISSN: 1085-7117. DOI: 10.1198/108571105x28183.

Salehi M, M (2004) Optimal sampling design under a spatial correlation model, Journal of Statistical Planning and Inference, 118(1-2), pp.9-18, ISSN: 0378-3758. DOI: 10.1016/s0378-3758(02)00403-2.

Salehi M, M and Seber, GAF (2004) A general inverse sampling scheme and its application to adaptive cluster sampling, Australian and New Zealand Journal of Statistics, 46(3), pp.483-494, ISSN: 1369-1473. DOI: 10.1111/j.1467-842x.2004.00345.x.

Salehi, MM (2003) Comparison between Hansen-Hurwitz and Horvitz-Thompson estimators for adaptive cluster sampling, Environmental and Ecological Statistics, 10(1), pp.115-127, ISSN: 1352-8505. DOI: 10.1023/a:1021989509323.

Salehi, MM and Seber, GAF (2002) Unbiased estimators for restricted adaptive cluster sampling, Australian and New Zealand Journal of Statistics, 44(1), pp.63-74, ISSN: 1369-1473. DOI: 10.1111/1467-842X.00208.

Salehi, MM and Seber, GAF (2001) Theory & Methods: A New Proof of Murthy's Estimator which Applies to Sequential Sampling, Australian & New Zealand Journal of Statistics, 43(3), pp.281-286, ISSN: 1369-1473. DOI: 10.1111/1467-842x.00174.

Salehi Marzijarani, M (1999) Rao-Blackwell versions of the Horvitz-Thompson and Hansen-Hurwitz in adaptive cluster sampling, Environmental and Ecological Statistics, 6(2), pp.183-195, ISSN: 1352-8505. DOI: 10.1023/a:1009670205509.

M, MS and Seber, GAF (1997) Two-Stage Adaptive Cluster Sampling, Biometrics, 53(3), pp.959-959, ISSN: 0006-341X. DOI: 10.2307/2533556.

Mohammad Salehi, M and Seber, GAF (1997) Adaptive cluster sampling with networks selected without replacement, Biometrika, 84(1), pp.209-219, ISSN: 0006-3444. DOI: 10.1093/biomet/84.1.209.



Conferences

Panahbehagh, B, Smith, DR, Salehi, MM, Hornbach, DJ, Brown, JA (2011) Multi-species attributes as the condition for adaptive sampling of rare species using two-stage sequential sampling with an auxiliary variable. In , Modsim 2011 19th International Congress on Modelling and Simulation Sustaining Our Future Understanding and Living with Uncertainty, pp.2093-2099.

Brown, JA, Salehi, MM, Moradi, M, Panahbehagh, B, Smith, DR (2011) Adaptive and unequal probability survey designs for environmental management. In , Modsim 2011 19th International Congress on Modelling and Simulation Sustaining Our Future Understanding and Living with Uncertainty, pp.2071-2077.



Chapters

Seber, GAF and Salehi, MM (2025) Adaptive Sampling. In International Encyclopedia of Statistical Science, Springer Berlin Heidelberg, pp.21-25, ISBN: 9783662693582. DOI: 10.1007/978-3-662-69359-9_11.



Other

F. Seber, GA and Salehi M, M Adaptive Sampling, AbstractAnimal populations are often highly clustered. For example, fish can form large, widely scattered schools with few fish in between. Even rare species of animals may form small groups that are hard to find. Applying standard sampling methods such as simple random sampling of plots to such a population could yield little information, with most of the plots being empty. Adaptive sampling is based on the simple idea that when some animals are located on a sample plot, the neighboring plots (and possibly their neighbors as well) are added to the sample; in this way, the whole cluster can be sampled. The scheme lends itself to a variety of modifications, for example, sampling with and without replacement, sequential and inverse sampling, stratified sampling, two‐stage sampling, and so‐called adaptive allocation, as well as extensions to multivariate data and incomplete detectability.. DOI: 10.1002/9781118445112.stat05692.

Seber, GAF and Mohammad Salehi, M Adaptive Sampling, AbstractAnimal populations are often highly grouped. For example, fish can form large, widely scattered schools with few fish in between. Even rare species of animals may form small groups that are hard to find. Applying standard sampling methods such as simple random sampling of plots to such a population could yield little information, with most of the plots being empty. Density estimation and physiological information based on this meagre information will have poor precision. Adaptive sampling is a method of unequal probability sampling based on the simple idea that when some animals are located on a sample plot, the neighboring plots (and possibly their neighbors as well) are added to the sample; in this way, the whole group can be sampled. The scheme lends itself to a variety of modifications, for example, sampling with and without replacement, sequential and inverse sampling, stratified sampling, two‐stage sampling, and the so‐called adaptive allocation, as well as extensions to order statistics, multivariate data, incomplete detectability, and super‐population models.. DOI: 10.1002/9781118445112.stat05692.pub2.



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