random processes and monte carlo simulation

... risks, and a quicker method of generating multiple model outcomes that you can analyze This is where Monte Carlo simulation comes in handy WHAT IS MONTE CARLO SIMULATION? What we mean by "simulation? " ... available simulation add-in for Excel is Crystal Ball 2000, which will be used in this example How did Monte Carlo simulation get its name? Monte Carlo simulation was named for Monte Carlo, Monaco, ... wheels, dice, and slot machines, exhibit random behavior Copyright © 2000, Decisioneering, Inc All rights reserved The random behavior in games of chance is similar to how Monte Carlo simulation...

Ngày tải lên: 08/04/2014, 12:08

... system, or population Simulation and Monte Carlo: With applications in finance and MCMC © 2007 John Wiley & Sons, Ltd J S Dagpunar Introduction to simulation and Monte Carlo Since simulations provide ... Introduction to simulation and Monte Carlo 1.1 Evaluating a definite integral 1.2 Monte Carlo is integral estimation 1.3 An example 1.4 A simulation using Maple 1.5 Problems 13 Uniform random numbers ... the left of = 1 Introduction to simulation and Monte Carlo A simulation is an experiment, usually conducted on a computer, involving the use of random numbers A random number stream is a sequence...

Ngày tải lên: 07/03/2014, 15:20

... Financial Models and Their Monte Carlo Simulation 53 Masaaki Kijima and Chun Ming Tam Chapter Monte- Carlo- Based Robust Procedure for Dynamic Line Layout Problems 87 Wai Kin (Victor) Chan and Charles ... is the measurand estimate, U ( y ) is the expanded uncertainty obtained by the GUM approach and ylow and yhigh are the low and high endpoints of the PDF obtained by the Monte Carlo simulation for ... Diffusion in Various Geometries and Application to Chemistry and Biology 193 Ianik Plante and Francis A Cucinotta Chapter 10 Kinetic Monte Carlo Simulation in Biophysics and Systems Biology 227 Subhadip...

Ngày tải lên: 16/03/2014, 12:20

... of light materials (such as paper, plastic, aluminum and thin stainless steel), and the results between the data of theoretical simulation and those of experimental measurements are compared together ... rate versus thickness between simulation by MCNP and experimental measurement for yellow paper Fig Comparison of count rate versus thickness between simulation by MCNP and experimental measurement ... rate versus thickness between simulation by MCNP and experimental measurement for white paper Fig Comparison of count rate versus thickness between simulation by MCNP and experimental measurement...

Ngày tải lên: 22/03/2014, 11:20

... angle and the possibility of reflection, transmission at surfaces Fig indicates the flowchart of photon movement in a biological sample Fig Flowchart for Monte Carlo simulations Monte Carlo simulations ... on MC simulations and DSP N.T Anh et al / VNU Journal of Science, Mathematics - Physics 26 (2010) 61-70 67 The measurement to verify optical parameters based on Monte Carlo simulations and the ... by MC simulations The measurement for µ a , µ s and g by Monte Carlo simulations with different milk concentrations is presented in Fig 11 By increasing the concentrations, both absorption and...

Ngày tải lên: 28/03/2014, 13:20

... of light materials (such as paper, plastic, aluminum and thin stainless steel), and the results between the data of theoretical simulation and those of experimental measurements are compared together ... rate versus thickness between simulation by MCNP and experimental measurement for yellow paper Fig Comparison of count rate versus thickness between simulation by MCNP and experimental measurement ... rate versus thickness between simulation by MCNP and experimental measurement for white paper Fig Comparison of count rate versus thickness between simulation by MCNP and experimental measurement...

Ngày tải lên: 21/07/2014, 16:21

... system, or population Simulation and Monte Carlo: With applications in finance and MCMC © 2007 John Wiley & Sons, Ltd J S Dagpunar Introduction to simulation and Monte Carlo Since simulations provide ... Introduction to simulation and Monte Carlo 1.1 Evaluating a definite integral 1.2 Monte Carlo is integral estimation 1.3 An example 1.4 A simulation using Maple 1.5 Problems 13 Uniform random numbers ... the left of = 1 Introduction to simulation and Monte Carlo A simulation is an experiment, usually conducted on a computer, involving the use of random numbers A random number stream is a sequence...

Ngày tải lên: 09/08/2014, 16:21

... (12 microseconds) and ‘r2’ (16 microseconds), taking approximately 17 microseconds per random number The seed is set using the command ‘randomize(integer)’ before invoking ‘rand()’ Maple also ... f x = e− on support x Simulation and Monte Carlo: With applications in finance and MCMC © 2007 John Wiley & Sons, Ltd J S Dagpunar 38 General methods for generating random variates Solution ... = P k−1 > k−1 As an example of this, 1000 random numbers were sampled using the Maple random number generator, ‘rand()’ Table 2.2 gives the observed and expected frequencies based upon k = 10...

Ngày tải lên: 09/08/2014, 16:21

... implement and reasonably fast in execution We start by considering two independent standard normal random variables, X1 and X2 The joint density is fX1 X2 x1 x2 = − e Simulation and Monte Carlo: ... the c n √ √ random variables nX/ − X and nY/ − Y are distributed as Student’s t with n degrees of freedom Are these two random variables independent? Given two random numbers R1 and R2 derive ... Appendix 5.2 For given n, and a, a simulation sampled j j = 5000 Table 5.1 shows the resulting and e.s.e The standard error for a naive Monte Carlo simulation is − /5000 and this may be estimated...

Ngày tải lên: 09/08/2014, 16:21

... Wiener process, will be described Simulation and Monte Carlo: With applications in finance and MCMC © 2007 John Wiley & Sons, Ltd J S Dagpunar 108 Simulation and finance 6.1 Brownian motion t ≥ ... queue simulation in Problem Write a Maple program and investigate the variance reduction achieved for different parameter values Write procedures for naive and conditional Monte Carlo simulations ... good stratification and control variable Using K = 50, N = 400, M = 20 seed = 566309 it is found that AS = 93055 (5.32) and ese AS = 00223 Using naive Monte Carlo with the same random number stream,...

Ngày tải lên: 09/08/2014, 16:21

... Fishman (1978), Law and Kelton (2000), and Pidd (1998) Simulation and Monte Carlo: With applications in finance and MCMC © 2007 John Wiley & Sons, Ltd J S Dagpunar 136 Discrete event simulation 7.1 ... some standard discrete event stochastic processes and then move on to examples of nonstandard processes We not deal with the simulation of large scale systems such as complex manufacturing processes ... = and is the empty set Let N C and N E denote the number of randomly occuring points in C and E respectively Suppose there exists a positive constant , such that, for all such C and E N C and...

Ngày tải lên: 09/08/2014, 16:21

... a random walk algorithm with Y = x+ 1/2 Z where 1/2 1/2 = and Z is a column of i.i.d standard normal random variables An independence sampler takes q y x = q y , so the distribution of the candidate ... hyperparameters, , and , is based upon the belief that the prior marginal expectation and standard deviation of any 170 Markov chain Monte Carlo prior and posterior densities prior and posterior densities ... suppress output of every Xn To obtain a random number in [0,1) insert R = x/61 Answers: (a) = 60, (b) = 30 Simulation and Monte Carlo: With applications in finance and MCMC © 2007 John Wiley & Sons,...

Ngày tải lên: 09/08/2014, 16:21

... describe, fit, importdata, random, statevalf, statplots, transform] > randomize(135);n:=1000; 135 n:=1000 Simulation and Monte Carlo: With applications in finance and MCMC Ó 2007 John Wiley & ... calls the random number generator ‘schrage’ The final execution group sets an (initial) seed and calls ‘expon’ three times Simulation and Monte Carlo: With applications in finance and MCMC Ó ... independent times between starting at the point ðx0 ; y0 Þ and landing in the treacle The function stats [random, normald](1) creates a random standard normal deviate 215 216 6 6 6 6 6 6 6 6 6 6 6 Appendices...

Ngày tải lên: 09/08/2014, 16:21

... STANDARD RANDOM NORMAL 6 6 # DEVIATE, USING THE POLAR BOX MULLER METHOD 6 6 # SET i to ’ false’ ON FIRST CALL Note that i and 4 Appendix 4: Random variate generators (standard distributions) Simulation ... randomize(13753);asiannaive(0.05,50,0.3,1,16,25000,50); 6 randomize(13753);asiannaive(0.05,50,0.3,1,16,25000,45); 6 randomize(13753);asiannaive(0.05,50,0.1,1,16,25000,55); 6 randomize(13753);asiannaive(0.05,50,0.1,1,16,25000,50); 6 randomize(13753);asiannaive(0.05,50,0.1,1,16,25000,45); ... ‘standard error’ ¼ 0.02797125535 Now replace r by À r and theta1_hat by theta2_hat in the print statement of procedure ‘theta1_2’ and run the simulation again with the same seed > seed:=randomize(341):...

Ngày tải lên: 09/08/2014, 16:21

... t[1]-clock>alpha then; randomize(seed2); seed2:=rand();# THIS RANDOM NUMBER IS GENERATED BUT NOT USED! THIS IS DONE TO PRESERVE 1-1 CORRESPONDENCE BETWEEN RANDOM NUMBERS AND PATIENTS’ LENGTHS ... short:=short+t[1]–clock; randomize(seed2); seed2:=rand( ); r2:=evalf(1/1000000000000*seed2); t[1]:=clock+(–ln(r2))^b1/m; t:=sort(t); q:=0; end if; if q=1 and nocc=n and a

Ngày tải lên: 09/08/2014, 16:21

... iterations; for i from to k do; r1:=evalf(rand()/10^12);r2:=evalf(rand()/10^12);r3:=evalf (rand()/10^12);r4:=evalf(rand()/10^12); # Sample candidate point (ap,bp) and compute likelihood (L2)for (ap,bp); ... prior and posterior densities prior and posterior densities 2e2 1e2 6 lambda[1] lambda[2] 2 6 prior and posterior densities prior and posterior densities 1e2 1e2 6 lambda[3] lambda[4] 2 prior and ... densities prior and posterior densities 6 6 lambda[5] 0 lambda[6] 1 prior and posterior densities prior and posterior densities 6 6 lambda[7] lambda[8] 4 prior and posterior densities prior and posterior...

Ngày tải lên: 09/08/2014, 16:21

Ngày tải lên: 14/11/2014, 08:17

... MONTE CARLO SIMULATION OF MOLECULES AND IONS IN LIQUID WATER MICHAEL YUDISTIRA PATUWO (B.Sc.(Hons), NUS) A THESIS ... F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F Molecular Monte Carlo Simulation PFI PFP Simulation of Neutral Molecules QFI QFP QFQ QFR QFS QFT QFU QFV QFW i iv vii ix ... interactions due to both electronic and nuclear spin are generally too small to be considered in the context of intermolecular forces, and they are often safely and reasonably neglected Organic...

Ngày tải lên: 10/09/2015, 15:49

... presence of stearate (SA) Using the Monte Carlo procedure described in the Materials and methods, 1000 synthetic sample sets were generated for each experimental setting and the estimated synthetic parameters ... reported in the present study for oleate and arachidonate (10–65 lm) Concluding remarks: advantages of progress curve analysis combined with Monte Carlo simulation Our findings illustrate the general ... measured points for exactly the same enzyme and modulator concentrations) and further expanded the ideas for computer-intensive procedures in time-course simulations [12–14] The global fit of the...

Ngày tải lên: 18/02/2014, 17:20

... VI.ToC Monte Carlo In the Concert-room—The Gambling-saloons—The Tables—The moth and the candle—The true story of Monte Carlo An International grievance and disgrace We reached Monte Carlo in time ... should be the land of our pilgrimage Should we cross the Pyrenees and traverse Spain, visiting Madrid and the Escurial en route to Seville, and thence through Andalusia and Granada, and home by ... about Monte Carlo, when gambling, to a frightful extent, is carried on at our clubs and stock exchanges in England? I can only answer, two wrongs can never make one right; besides, Monte Carlo...

Ngày tải lên: 15/03/2014, 12:20