# Normal distribution function in Matlab

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JACINTA ONWUKA on 20 Nov 2020
Commented: Star Strider on 20 Nov 2020
p was changed to a normal and is giving me the error "Matrix dimensions must agree." in tau.
t0=0;
L=1;
tend=100;
I=linspace(0, 1);
p = normrnd(0.0001,0.0001,[1,10])
beta=0.1;
delta=1;
I1=0.25;
epsilon=1;
tau = (1/(beta*(L+delta*p)))*log((L*(I1+delta*p))/(delta*p*(L-I1)))
t1=linspace(0,tau);
t2=linspace(tau,tend);
I2= (L*delta*p*(exp (beta*(L+delta*p)*t1)-1)) ./ (L + delta*p* exp(beta*(L+delta*p)*t1));
I3= (L* (I1+delta*p)*exp((epsilon*beta)*(L+delta*p)*(t2-tau))-...
delta*p*(L -I1))./(L-I1+(I1+delta*p)*exp(epsilon*beta*(L+delta*p)*(t2-tau(delta))));
plot(t1,I2,'k',t2,I3,'k');

Star Strider on 20 Nov 2020
Use element-wise operations on every multiplication, division (and exponentiation, although not used here).
This works:
tau = (1./(beta.*(L+delta.*p))).*log((L.*(I1+delta.*p))./(delta.*p.*(L-I1)));
See Array vs. Matrix Operations for details.
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Star Strider on 20 Nov 2020
Provide all scalar inputs to linspace.
Perhaps:
t1=linspace(0, max(tau), numel(tau));
t2=linspace(min(tau), max(tau), tend);
These are obviously just guesses.
I have no idea what you are doing, so make appropriate changes to get the result you want.

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