How do I estimate a function to obtain its different values while varying one of its parameter? So that I can obtain my estimate in form of the parameter am varying[nuA], I declared the parameter as a symbol and later declare it as the interval.
1 vue (au cours des 30 derniers jours)
Afficher commentaires plus anciens
Mayowa Micheal Ojo
le 28 Oct 2018
Commenté : Rena Berman
le 12 Déc 2019
clear all
clc
%%%%%%%%%%%%%%Declaring of Parameter values %%%%%%%%%%%%%%
syms nuA
% nuA=0.14868;
mu=1/(56*365);
pi=mu*182202000*(1/365);
omegaA=(1/5)*(1/365);
eta=1;
epsilon=((1.90)/2);
betaA=0.43296; betac=0.43296;
gammacA= 0.1118; gammacc=0.1118;
gammaIA=0.1128; gammaIc=0.1128;
gammacAc=0.1118; gammaIAc=0.1128;
sigmaA=0.0548; sigmac=0.0548; sigmaAc=0.0548;
kappaA = 0.0031; kappac = 0.0031; kappaAc = 0.0031;
deltaA=0.1923; deltac=0.1923; deltaAc=0.1923;
%%%%%%%%%%%%%%%Declaring the representations %%%%%%%%%%%%%
k1=(nuA+mu);
k2=(omegaA+mu);
k3=(sigmaA+ gammacA + mu);
k4=(gammaIA+ mu+ deltaA);
k5=(kappaA+mu);
k6=(sigmac+ gammacc + mu);
k7=(gammaIc+ mu + deltac);
k8=(kappac+mu);
k9=(sigmaAc+gammacAc+mu);
k10=(gammaIAc+mu+deltaAc);
k11=(kappaAc+mu);
p=(1-epsilon);
P1=(k4*gammacA+gammaIA*sigmaA);
P2=(k7*gammacc+gammaIc*sigmac);
lambdaA=0.0811;
a=(pi*k4*k5*p)+(pi*k5*sigmaA*p)+(pi*p*P1);
b=(pi*k2*k4*k5)+(pi*k3*k4*k5*p)+(pi*k4*k5*p*nuA)+(pi*k2*k5*sigmaA)+(pi*k5*sigmaA*p*nuA)+(pi*P1*k2)+(pi*P1*p*nuA)-(betaA*eta*k4*k5*p)-(betaA*pi*k5*sigmaA*p);
c=(pi*k2*k3*k4*k5)+(pi*k3*k4*k5*nuA)-(betaA*eta*pi*k4*k5*P1*nuA)-(betaA*eta*pi*k2*k4*k5)-(betaA*pi*k2*k5*sigmaA)-(betaA*pi*k5*sigmaA*p*nuA);
SA=pi*k3*k4*k5*(p*lambdaA+k2)/((k3*k4*k5*(lambdaA+k1)*(p*lambdaA+k2)-k3*k4*k5*omegaA*nuA)-(lambdaA*kappaA*P1*(p*lambdaA+k2+p*nuA))); %Susceptible population%
VAA=nuA*pi*k3*k4*k5/((k3*k4*k5*(lambdaA+k1)*(p*lambdaA+k2)-k3*k4*k5*omegaA*nuA)-(lambdaA*kappaA*P1*(p*lambdaA+k2+p*nuA))); %Vaccinated population%
NA=(pi*k3*k4*k5*(p*lambdaA+k2+nuA)+(lambdaA*pi*k4*k5+lambdaA*pi*sigmaA*k5+lambdaA*pi*P1)*(p*lambdaA+k2+p*nuA))/((k3*k4*k5*(lambdaA+k1)*(p*lambdaA+k2)-k3*k4*k5*omegaA*nuA)-(lambdaA*kappaA*P1*(p*lambdaA+k2+p*nuA))); %Total population%
%%%%%%%%%%%Evaluating Invasion Reproduction Number of A over C %%%%%%%%%
nA=[0.1:0.2:2];
RcA= betac*((eta*k7+sigmac)*(SA+VAA))/(k6*k7*NA)
2 commentaires
Stephen23
le 16 Nov 2019
Original Question (from Google Cache) by Mayowa Micheal Ojo "How do I estimate a function to obtain its different values while varying one of its parameter? So that I can obtain my estimate in form of the parameter am varying[nuA], I declared the parameter as a symbol and later declare it as the interval.":
clear all
clc
%%%%%%%%%%%%%%Declaring of Parameter values %%%%%%%%%%%%%%
syms nuA
% nuA=0.14868;
mu=1/(56*365);
pi=mu*182202000*(1/365);
omegaA=(1/5)*(1/365);
eta=1;
epsilon=((1.90)/2);
betaA=0.43296; betac=0.43296;
gammacA= 0.1118; gammacc=0.1118;
gammaIA=0.1128; gammaIc=0.1128;
gammacAc=0.1118; gammaIAc=0.1128;
sigmaA=0.0548; sigmac=0.0548; sigmaAc=0.0548;
kappaA = 0.0031; kappac = 0.0031; kappaAc = 0.0031;
deltaA=0.1923; deltac=0.1923; deltaAc=0.1923;
%%%%%%%%%%%%%%%Declaring the representations %%%%%%%%%%%%%
k1=(nuA+mu);
k2=(omegaA+mu);
k3=(sigmaA+ gammacA + mu);
k4=(gammaIA+ mu+ deltaA);
k5=(kappaA+mu);
k6=(sigmac+ gammacc + mu);
k7=(gammaIc+ mu + deltac);
k8=(kappac+mu);
k9=(sigmaAc+gammacAc+mu);
k10=(gammaIAc+mu+deltaAc);
k11=(kappaAc+mu);
p=(1-epsilon);
P1=(k4*gammacA+gammaIA*sigmaA);
P2=(k7*gammacc+gammaIc*sigmac);
lambdaA=0.0811;
a=(pi*k4*k5*p)+(pi*k5*sigmaA*p)+(pi*p*P1);
b=(pi*k2*k4*k5)+(pi*k3*k4*k5*p)+(pi*k4*k5*p*nuA)+(pi*k2*k5*sigmaA)+(pi*k5*sigmaA*p*nuA)+(pi*P1*k2)+(pi*P1*p*nuA)-(betaA*eta*k4*k5*p)-(betaA*pi*k5*sigmaA*p);
c=(pi*k2*k3*k4*k5)+(pi*k3*k4*k5*nuA)-(betaA*eta*pi*k4*k5*P1*nuA)-(betaA*eta*pi*k2*k4*k5)-(betaA*pi*k2*k5*sigmaA)-(betaA*pi*k5*sigmaA*p*nuA);
SA=pi*k3*k4*k5*(p*lambdaA+k2)/((k3*k4*k5*(lambdaA+k1)*(p*lambdaA+k2)-k3*k4*k5*omegaA*nuA)-(lambdaA*kappaA*P1*(p*lambdaA+k2+p*nuA))); %Susceptible population%
VAA=nuA*pi*k3*k4*k5/((k3*k4*k5*(lambdaA+k1)*(p*lambdaA+k2)-k3*k4*k5*omegaA*nuA)-(lambdaA*kappaA*P1*(p*lambdaA+k2+p*nuA))); %Vaccinated population%
NA=(pi*k3*k4*k5*(p*lambdaA+k2+nuA)+(lambdaA*pi*k4*k5+lambdaA*pi*sigmaA*k5+lambdaA*pi*P1)*(p*lambdaA+k2+p*nuA))/((k3*k4*k5*(lambdaA+k1)*(p*lambdaA+k2)-k3*k4*k5*omegaA*nuA)-(lambdaA*kappaA*P1*(p*lambdaA+k2+p*nuA))); %Total population%
%%%%%%%%%%%Evaluating Invasion Reproduction Number of A over C %%%%%%%%%
nA=[0.1:0.2:2];
RcA= betac*((eta*k7+sigmac)*(SA+VAA))/(k6*k7*NA)
Réponse acceptée
Walter Roberson
le 28 Oct 2018
Modifié(e) : Walter Roberson
le 28 Oct 2018
RcA_numeric = double( subs(RcA, nuA, nA) );
3 commentaires
Plus de réponses (0)
Voir également
Catégories
En savoir plus sur Ordinary Differential Equations dans Help Center et File Exchange
Produits
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!