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Journal articles on the topic 'Neyman-Scott'

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Published: 10 December 2022

Last updated: 21 February 2023

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1

Kim, Nam Hee, and Yongku Kim. "A statistical inference for Neyman-Scott Rectangular Pulse model." Korean Journal of Applied Statistics 29, no. 5 (August 31, 2016): 887–96. http://dx.doi.org/10.5351/kjas.2016.29.5.887.

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2

Brillinger, David R. "Synthetic plots: some history and examples." São Paulo Journal of Mathematical Sciences 8, no. 2 (December 12, 2014): 157. http://dx.doi.org/10.11606/issn.2316-9028.v8i2p157-168.

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Jerzy Neyman and Elizabeth Scott developed the idea of synthetic plots. These plots are a display of the data values of an experiment side by side with a display of simulated data values, with the simulation-based on a considered stochastic model. The Neyman and Scott work concerned the distribution of galaxies on the celestial sphere. A review of their wo is presented here followed by personal examples from hydrology, neuroscience, and animal motion.

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3

Jeong, Chang-Sam. "Study of Direct Parameter Estimation for Neyman-Scott Rectangular Pulse Model." Journal of Korea Water Resources Association 42, no. 11 (November 30, 2009): 1017–28. http://dx.doi.org/10.3741/jkwra.2009.42.11.1017.

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4

Brand, Michael. "MML Is Not Consistent for Neyman-Scott." IEEE Transactions on Information Theory 66, no. 4 (April 2020): 2533–48. http://dx.doi.org/10.1109/tit.2019.2943464.

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5

JALILIAN, ABDOLLAH H., and MOHAMMAD Q. VAHIDI-ASL. "Residual Analysis for Inhomogeneous Neyman-Scott Processes." Scandinavian Journal of Statistics 38, no. 4 (May 13, 2011): 617–30. http://dx.doi.org/10.1111/j.1467-9469.2011.00731.x.

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6

SMALL, CHRISTOPHER G., and D. J. MURDOCH. "Nonparametric Neyman-Scott problems: Telescoping product methods." Biometrika 80, no. 4 (1993): 763–79. http://dx.doi.org/10.1093/biomet/80.4.763.

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7

Alcocer Yamanaka, Víctor Hugo, and Velitchko G. Tzatchkov. "Neyman-Scott-based water distribution network modelling." Ingeniería e Investigación 32, no. 3 (September 1, 2012): 32–36. http://dx.doi.org/10.15446/ing.investig.v32n3.35937.

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Residential water demand is one of the most difficult parameters to determine when modelling drinking water distribution networks. It has been proven to be a stochastic process which can be characterised as a series of rectangular pulses having set intensity, duration and frequency. Such parameters can be determined using stochastic models such as the Neyman-Scott rectangular pulse model (NSRPM). NSRPM is based on resolving a non-linear optimisation problem involving theoretical moments of the synthetic demand series (equiprobable) and of the observed moments (field measurements) statistically establishing the measured demand series. NSRPM has been applied to generating local residential demand. However, this model has not been validated for a real distribution network with residential demand aggregation, or compared to traditional methods (which is dealt with here). This paper compares the results of synthetic stochastic demand series (calculated using NSRPM applied to determining pressure and flow rate) to results obtained using traditional simulation methods using the curve of hourly variation in demand and to actual pressure and flow rate measurements. The Humaya sector of Culiacan, Sinaloa, Mexico, was used as study area.

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8

Lee, Jeongjin, and Yongku Kim. "A spatial analysis of Neyman-Scott rectangular pulses model using an approximate likelihood function." Journal of the Korean Data and Information Science Society 27, no. 5 (September 30, 2016): 1119–31. http://dx.doi.org/10.7465/jkdi.2016.27.5.1119.

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9

Bhanja, Joydeep, and Malay Ghosh. "The Neyman-Scott Phenomenon in Generalized Linear Models and Overdispersed Exponential Families." Calcutta Statistical Association Bulletin 44, no. 1-2 (March 1994): 29–40. http://dx.doi.org/10.1177/0008068319940103.

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In fixed effects balanced one-way analysis of variance models with homoscedastic normal errors, the maximum likelihood estimator (MLE) of the error variance is inconsistent as the cell-size remains fixed but the number of cells grows to infinity. This is the famous Neymnn-Scott phenomenon. The present paper shows that the Neyman-Scott phenomenon continues to hold for estimating the scale parameter in the canonical version of generalized linear models when the number of nuisance parameters grows to infinity. A similar result holds for overdispersed exponential faruily of distributions. It is also pointed out how the conditional MLE in such cases does not suffer from the inconsistency problem. The relationship between the conditional score function and the corrected score function in general mixture models is also pointed out. The Neyman-Scott phenomenon is also shown to hold for the two-parameter exponential family typically used for modelling overdispersion.

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10

Najari, Nader, and Mohammad Q. Vahidi Asl. "Neyman–Scott process with alpha-skew-normal clusters." Environmental and Ecological Statistics 28, no. 1 (January 8, 2021): 73–86. http://dx.doi.org/10.1007/s10651-020-00476-y.

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11

Pace, Luigi, Alessandra Salvan, and Laura Ventura. "Remedying the Neyman–Scott phenomenon in model discrimination." Journal of Statistical Computation and Simulation 81, no. 6 (June 2011): 749–57. http://dx.doi.org/10.1080/00949650903471015.

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12

Kim, Gwangseob, Hyungon Cho, and Jaeeung Yi. "Parameter Estimation of the Neyman-Scott Rectangular Pulse Model Using a Differential Evolution Method." Journal of Korean Society of Hazard Mitigation 12, no. 4 (August 31, 2012): 187–94. http://dx.doi.org/10.9798/kosham.2012.12.4.187.

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13

Coeurjolly, Jean-François, and Patricia Reynaud-Bouret. "A concentration inequality for inhomogeneous Neyman–Scott point processes." Statistics & Probability Letters 148 (May 2019): 30–34. http://dx.doi.org/10.1016/j.spl.2018.12.003.

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14

Shin, Ju-Young, Kyoung-Won Joo, and Jun-Haeng Heo. "A Study of New Modified Neyman-Scott Rectangular Pulse Model Development Using Direct Parameter Estimation." Journal of Korea Water Resources Association 44, no. 2 (February 28, 2011): 135–44. http://dx.doi.org/10.3741/jkwra.2011.44.2.135.

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15

Popov, V. S. "On the Luminosity Function of Elliptical Galaxies." Symposium - International Astronomical Union 127 (1987): 461–62. http://dx.doi.org/10.1017/s0074180900185742.

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Originally the luminosity function of galaxies was derived by E. Hubble (1936). Later studies are by Holmberg (1950), Zwicky (1957, 1964), Kiang (1961), Neyman and Scott (1962), Van den Bergh (1961), Pskovsky (1965), Nezhinsky and Osipkov (1967, 1969), Genkina (1969), Popov (1980), Tammann (1984), and others.

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16

Leonard, M., A. Metcalfe, M. Lambert, and G. Kuczera. "Implementing a space-time rainfall model for the Sydney region." Water Science and Technology 55, no. 4 (February 1, 2007): 39–47. http://dx.doi.org/10.2166/wst.2007.093.

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This paper investigates a Spatial Neyman–Scott Rectangular Pulse (SNSRP) model, which is one of only a few models capable of continuous simulation of rainfall in both space and time. The SNSRP is a spatial extension of the Neyman–Scott Rectangular Pulse model at a single point. The model is highly idealized having six parameters: storm arrival, cell arrival, cell radius, cell lifetime and two cell intensity parameters. A spatial interpolation of the scale parameter is used so that the model can be simulated continuously in space, rather than as a multi-site model. The parameters are calibrated using least-squares fits to statistical moments based on data aggregated to hourly and daily totals. The SNSRP model is calibrated to a very large network of 85 gauges over metropolitan Sydney and shows a good agreement to calibrated statistics. A simulation of 50 replicates over the region compares favourably to several observed temporal statistics, with an example given for one site. A qualitative discussion of the simulated spatial images demonstrates the underlying structure of non-advecting cylindrical cells.

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17

Cowpertwait, Paul. "A Neyman-Scott model with continuous distributions of storm types." ANZIAM Journal 51 (April 10, 2010): 97. http://dx.doi.org/10.21914/anziamj.v51i0.3025.

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18

MONDONEDO, Carlo Arturo, Yasuto TACHIKAWA, and Kaoru TAKARA. "EVALUATION OF THE QUANTILES OF THE NEYMAN-SCOTT RAINFALL MODEL." PROCEEDINGS OF HYDRAULIC ENGINEERING 51 (2007): 79–84. http://dx.doi.org/10.2208/prohe.51.79.

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19

Mrkvička, T. "Distinguishing Different Types of Inhomogeneity in Neyman–Scott Point Processes." Methodology and Computing in Applied Probability 16, no. 2 (August 7, 2013): 385–95. http://dx.doi.org/10.1007/s11009-013-9365-4.

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20

Tanaka, Ushio, and Yosihiko Ogata. "Identification and estimation of superposed Neyman–Scott spatial cluster processes." Annals of the Institute of Statistical Mathematics 66, no. 4 (February 14, 2014): 687–702. http://dx.doi.org/10.1007/s10463-013-0431-z.

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21

Tanaka, Ushio, Yosihiko Ogata, and Dietrich Stoyan. "Parameter Estimation and Model Selection for Neyman-Scott Point Processes." Biometrical Journal 50, no. 1 (February 2008): 43–57. http://dx.doi.org/10.1002/bimj.200610339.

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22

Park, Jaewoo, Won Chang, and Boseung Choi. "An interaction Neyman–Scott point process model for coronavirus disease-19." Spatial Statistics 47 (March 2022): 100561. http://dx.doi.org/10.1016/j.spasta.2021.100561.

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23

Foufoula-Georgiou, Efi, and Peter Guttorp. "Assessment of a class of Neyman-Scott models for temporal rainfall." Journal of Geophysical Research 92, no. D8 (1987): 9679. http://dx.doi.org/10.1029/jd092id08p09679.

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24

Calenda, G., and F. Napolitano. "Parameter estimation of Neyman–Scott processes for temporal point rainfall simulation." Journal of Hydrology 225, no. 1-2 (November 1999): 45–66. http://dx.doi.org/10.1016/s0022-1694(99)00133-x.

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25

Kopecký, Jiří, and Tomáš Mrkvička. "On the Bayesian estimation for the stationary Neyman-Scott point processes." Applications of Mathematics 61, no. 4 (August 2016): 503–14. http://dx.doi.org/10.1007/s10492-016-0144-8.

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26

Waagepetersen, Rasmus Plenge. "An Estimating Function Approach to Inference for Inhomogeneous Neyman-Scott Processes." Biometrics 63, no. 1 (November 13, 2006): 252–58. http://dx.doi.org/10.1111/j.1541-0420.2006.00667.x.

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27

Favre, A. C., A. Musy, and S. Morgenthaler. "Two-site modeling of rainfall based on the Neyman-Scott process." Water Resources Research 38, no. 12 (December 2002): 43–1. http://dx.doi.org/10.1029/2002wr001343.

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28

Stoyan, D. "Statistical estimation of model parameters of planar neyman-scott cluster processes." Metrika 39, no. 1 (December 1992): 67–74. http://dx.doi.org/10.1007/bf02613983.

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29

Lee, Chinsan, and Grace L. Yang. "A multitype decomposable age-dependent branching process and its applications." Journal of Applied Probability 32, no. 3 (September 1995): 591–608. http://dx.doi.org/10.2307/3215115.

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Asymptotic formulas for means and variances of a multitype decomposable age-dependent supercritical branching process are derived. This process is a generalization of the Kendall–Neyman–Scott two-stage model for tumor growth. Both means and variances have exponential growth rates as in the case of the Markov branching process. But unlike Markov branching, these asymptotic moments depend on the age of the original individual at the start of the process and the life span distribution of the progenies.

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30

Lee, Chinsan, and Grace L. Yang. "A multitype decomposable age-dependent branching process and its applications." Journal of Applied Probability 32, no. 03 (September 1995): 591–608. http://dx.doi.org/10.1017/s0021900200103067.

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Asymptotic formulas for means and variances of a multitype decomposable age-dependent supercritical branching process are derived. This process is a generalization of the Kendall–Neyman–Scott two-stage model for tumor growth. Both means and variances have exponential growth rates as in the case of the Markov branching process. But unlike Markov branching, these asymptotic moments depend on the age of the original individual at the start of the process and the life span distribution of the progenies.

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31

Yendra, Rado, Ari Pani Desvina, Rahmadeni Rahmadeni, Wan Zawiah Wan Zin, Abdul Aziz Jemain, and Ahmad Fudholi. "Neyman Scott Rectangular Pulse Modeling for Storm Rainfall Analysis in Peninsular Malaysia." Research Journal of Applied Sciences, Engineering and Technology 11, no. 8 (November 15, 2015): 841–46. http://dx.doi.org/10.19026/rjaset.11.2093.

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32

Cowpertwait, P. S. P., and P. E. O'Connell. "A Regionalised Neyman-Scott Model of Rainfall with Convective and Stratiform Cells." Hydrology and Earth System Sciences 1, no. 1 (March 31, 1997): 71–80. http://dx.doi.org/10.5194/hess-1-71-1997.

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Abstract. A single-site Neyman-Scott Poisson cluster model of rainfall, with convective and stratiform cells, is fitted to data for 112 sites scattered throughout the UK using harmonic variables to account for seasonality. The model is regionalised by regressing the estimates of the harmonic variables on site dependent variables (e.g. altitude) to enable rainfall to be simulated at any ungauged site in the UK. An assessment of the residual errors indicates that the regression models can be used with reasonable confidence for urban sites. Furthermore, the regional variations of the model parameter estimates are found to be in agreement with meteorological knowledge and observation. Simulated I h extreme rainfalls are found to compare favourably with observed historical values, although some lack-of-fit is evident for higher aggregation levels.

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33

MONDONEDO, Carlo Arturo, Yasuto TACHIKAWA, and Kaoru TAKARA. "POT NORMALIZED VARIANCE PARAMETER SEARCH OF THE TEMPORAL NEYMAN-SCOTT RAINFALL MODEL." PROCEEDINGS OF HYDRAULIC ENGINEERING 52 (2008): 97–102. http://dx.doi.org/10.2208/prohe.52.97.

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34

Cowpertwait, Paul S. P. "Further developments of the neyman-scott clustered point process for modeling rainfall." Water Resources Research 27, no. 7 (July 1991): 1431–38. http://dx.doi.org/10.1029/91wr00479.

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35

Mrkvička, T., M. Muška, and J. Kubečka. "Two step estimation for Neyman-Scott point process with inhomogeneous cluster centers." Statistics and Computing 24, no. 1 (October 9, 2012): 91–100. http://dx.doi.org/10.1007/s11222-012-9355-3.

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36

Brown, B. "Clustering and abundance estimation for Neyman-Scott models and line transect surveys." Biometrika 85, no. 2 (June 1, 1998): 427–38. http://dx.doi.org/10.1093/biomet/85.2.427.

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37

Cowpertwait, P. S. P., C. G. Kilsby, and P. E. O'Connell. "A space-time Neyman-Scott model of rainfall: Empirical analysis of extremes." Water Resources Research 38, no. 8 (August 2002): 6–1. http://dx.doi.org/10.1029/2001wr000709.

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38

Møller, Jesper. "Shot noise Cox processes." Advances in Applied Probability 35, no. 3 (September 2003): 614–40. http://dx.doi.org/10.1239/aap/1059486821.

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Shot noise Cox processes constitute a large class of Cox and Poisson cluster processes in ℝd, including Neyman-Scott, Poisson-gamma and shot noise G Cox processes. It is demonstrated that, due to the structure of such models, a number of useful and general results can easily be established. The focus is on the probabilistic aspects with a view to statistical applications, particularly results for summary statistics, reduced Palm distributions, simulation with or without edge effects, conditional simulation of the intensity function and local and spatial Markov properties.

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39

Møller, Jesper. "Shot noise Cox processes." Advances in Applied Probability 35, no. 03 (September 2003): 614–40. http://dx.doi.org/10.1017/s0001867800012465.

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Shot noise Cox processes constitute a large class of Cox and Poisson cluster processes in ℝd, including Neyman-Scott, Poisson-gamma and shot noise G Cox processes. It is demonstrated that, due to the structure of such models, a number of useful and general results can easily be established. The focus is on the probabilistic aspects with a view to statistical applications, particularly results for summary statistics, reduced Palm distributions, simulation with or without edge effects, conditional simulation of the intensity function and local and spatial Markov properties.

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40

Burton, A., H. J. Fowler, S. Blenkinsop, and C. G. Kilsby. "Downscaling transient climate change using a Neyman–Scott Rectangular Pulses stochastic rainfall model." Journal of Hydrology 381, no. 1-2 (February 2010): 18–32. http://dx.doi.org/10.1016/j.jhydrol.2009.10.031.

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41

Cruz-Gonzalez, Mario, Iván Fernández-Val, and Martin Weidner. "Bias Corrections for Probit and Logit Models with Two-way Fixed Effects." Stata Journal: Promoting communications on statistics and Stata 17, no. 3 (September 2017): 517–45. http://dx.doi.org/10.1177/1536867x1701700301.

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In this article, we present the user-written commands probitfe and logitfe, which fit probit and logit panel-data models with individual and time unobserved effects. Fixed-effects panel-data methods that estimate the unobserved effects can be severely biased because of the incidental parameter problem (Neyman and Scott, 1948, Econometrica 16: 1–32). We tackle this problem using the analytical and jackknife bias corrections derived in Fernández-Val and Weidner (2016, Journal of Econometrics 192: 291–312) for panels where the two dimensions ( N and T) are moderately large. We illustrate the commands with an empirical application to international trade and a Monte Carlo simulation calibrated to this application.

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42

Riccardi, Gerardo Adrián. "Evaluación del modelo de Neyman-Scott para simulación de lluvia en un punto geográfico." Ingeniería del agua 12, no. 2 (June 30, 2005): 161. http://dx.doi.org/10.4995/ia.2005.2559.

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Se presenta una aplicación y evaluación del modelo de simulación de series de lluvia de Neyman-Scott de pulsos rectangulares, en su formulación original. Dicho modelo está basado en la teoría de procesos de punteo, en el cual se simula la estructura celular de los campos reales de precipitación preservando los parámetros estadísticos relevantes, en un amplio rango de las escalas de agregación temporal. Esta característica vinculada a la agregación temporal hace de estos modelos herramientas útiles en estudios hidrológicos, tales como producción de escurrimiento, infiltración, recarga de acuíferos, predicción de crecidas y sequías, simulación hidrológica continua, etc.. El modelo se sustenta en la descripción de un proceso de Poisson que fija el origen de los eventos, un proceso que fija el número de celdas de lluvias generadas en cada evento y un proceso que fija el origen temporal de cada celda. Además, cada celda tiene una duración aleatoria y una intensidad aleatoria. La aplicación del modelo fue realizada en la serie de registros de la estación pluviográfica Rosario Aero (Rosario, Argentina). Las series fueron analizadas en agrupamientos mensuales con el fin de preservar la estacionariedad. Las escalas de agregaciones temporales consideradas para la determinación de los parámetros del modelo fueron 0.5, 1, 2, 3, 4, 6, 12 y 24 horas, en tanto que para la evaluación de los resultados generados se consideraron además escalas de 48, 72 y 168 horas. La generación de series sintéticas mostró un importante nivel de aproximación entre estadísticos y variables muestrales y generadas, tales como media, varianza, estructura de correlación, probabilidad de lluvia cero y valores extremos.

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43

Yendra, Rado, Ari Pani Desvina, Rahmadeni Rahmadeni, Abdul Aziz Jemain, Wan Zawiah Wan Zin, and Ahmad Fudholi. "Rainfall Storm Modeling of Neyman-Scott Rectangular Pulse (NSRP) using Rainfall Cell Intensity Distributions." Research Journal of Applied Sciences, Engineering and Technology 11, no. 9 (November 25, 2015): 969–74. http://dx.doi.org/10.19026/rjaset.11.2136.

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44

Jalilian, Abdollah. "On the higher order product density functions of a Neyman–Scott cluster point process." Statistics & Probability Letters 117 (October 2016): 144–50. http://dx.doi.org/10.1016/j.spl.2016.05.003.

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45

Mondonedo, Carlo A., Yasuto Tachikawa, and Kaoru Takara. "Improvement of monthly and seasonal synthetic extreme values of the Neyman-Scott rainfall model." Hydrological Processes 24, no. 5 (February 28, 2010): 654–63. http://dx.doi.org/10.1002/hyp.7559.

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46

Lee, Jeonghoon, Ungtae Kim, Sangdan Kim, and Jungho Kim. "Development and Application of a Rainfall Temporal Disaggregation Method to Project Design Rainfalls." Water 14, no. 9 (April 27, 2022): 1401. http://dx.doi.org/10.3390/w14091401.

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A climate model is essential for hydrological designs considering climate change, but there are still limitations in employing raw temporal and spatial resolutions for small urban areas. To solve the temporal scale gap, a temporal disaggregation method of rainfall data was developed based on the Neyman–Scott Rectangular Pulse Model, a stochastic rainfall model, and future design rainfall was projected. The developed method showed better performance than the benchmark models. It produced promising results in estimating the rainfall quantiles for recurrence intervals of less than 20 years. Overall, the analysis results imply that extreme rainfall events may increase. Structural/nonstructural measures are urgently needed for irrigation and the embankment of new water resources.

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47

Brix, Anders. "Generalized Gamma measures and shot-noise Cox processes." Advances in Applied Probability 31, no. 4 (December 1999): 929–53. http://dx.doi.org/10.1239/aap/1029955251.

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A parametric family of completely random measures, which includes gamma random measures, positive stable random measures as well as inverse Gaussian measures, is defined. In order to develop models for clustered point patterns with dependencies between points, the family is used in a shot-noise construction as intensity measures for Cox processes. The resulting Cox processes are of Poisson cluster process type and include Poisson processes and ordinary Neyman-Scott processes.We show characteristics of the completely random measures, illustrated by simulations, and derive moment and mixing properties for the shot-noise random measures. Finally statistical inference for shot-noise Cox processes is considered and some results on nearest-neighbour Markov properties are given.

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48

Brix, Anders. "Generalized Gamma measures and shot-noise Cox processes." Advances in Applied Probability 31, no. 04 (December 1999): 929–53. http://dx.doi.org/10.1017/s0001867800009538.

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A parametric family of completely random measures, which includes gamma random measures, positive stable random measures as well as inverse Gaussian measures, is defined. In order to develop models for clustered point patterns with dependencies between points, the family is used in a shot-noise construction as intensity measures for Cox processes. The resulting Cox processes are of Poisson cluster process type and include Poisson processes and ordinary Neyman-Scott processes. We show characteristics of the completely random measures, illustrated by simulations, and derive moment and mixing properties for the shot-noise random measures. Finally statistical inference for shot-noise Cox processes is considered and some results on nearest-neighbour Markov properties are given.

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49

Ramirez, Jorge A., and Rafael L. Bras. "Conditional Distributions of Neyman-Scott Models for Storm Arrivals and Their Use in Irrigation Scheduling." Water Resources Research 21, no. 3 (March 1985): 317–30. http://dx.doi.org/10.1029/wr021i003p00317.

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50

Konecny, FRANZ. "On the estimation of the stochastic intensity and the parameters of neyman-scott trigger processes." Statistics 18, no. 1 (January 1987): 113–18. http://dx.doi.org/10.1080/02331888708801997.

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