How to Use Recurrence Formula for Least Square Method?

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In summary, the student is trying to solve a problem involving a differential equation, but does not know how to use a recorrence formula. They are seeking help in understanding the problem and in finding a solution.
  • #1
juaninf
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Hi all,

I am solving this http://rinconmatematico.com/foros/index.php/topic,35055.0.html", please i want one advice to solver this exercise, because I saw where it exercises only have one tabela, and and ask me to find the coefficients but this exercise have recurrence equation, this is my problem

help me Please
 
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  • #2
juaninf said:
Hi all,

I am solving this http://rinconmatematico.com/foros/index.php/topic,35055.0.html", please i want one advice to solver this exercise, because I saw where it exercises only have one tabela, and and ask me to find the coefficients but this exercise have recurrence equation, this is my problem

help me Please

Welcome to the PF. Could you please translate the text of the attachment? We will need an English translation in order to be of help. Also, could you please show us your attempt at solving the problem? We need to see your try before we can be of much tutorial help.
 
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  • #3
This is a problem :

Ordinary differential equation not linear in the variable [tex]\varphi[/tex] given by
[tex]\frac{d\varphi}{dt} = (a-b\varphi)\varphi[/tex]

where [tex]a[/tex] and[tex]b[/tex] are parameters of the model. Because these parameters are unknown seeks to adjust them so that the response of the model to represent a sequence of observed data on [tex]\varphi[/tex] . Table 2(attach)gives information on how [tex]\varphi[/tex] varies with time [tex]t[/tex]

Assume that it is acceptable to approximate the differential equation to describe the evolution of [tex]\varphi[/tex] by the following equation.

[tex]\varphi_{n+1} = (1+a\Delta t-b\Delta t\varphi_n)\varphi_n[/tex]

which is derived from considering [tex]\frac{d\varphi}{dt} \approx \frac{\varphi_{n+1}-\varphi_{n}}{\Delta t}[/tex] where [tex]\Delta t[/tex] represents the passage of time between [tex]t_{n+1}[/tex] e [tex]t_{n}[/tex] e to consider [tex]\varphi \approx \varphi_n[/tex] on the right side of the equation

Determine the parameters [tex]a[/tex] and [tex]b[/tex] by the method of least squares with polynomial approximation of degree 2 and 3. Compare the results that the model gives for [tex]t = 80 [/tex][tex]t = 100[/tex] in both cases

I able to find only with table(whitout this formula [tex]\varphi_{n+1} = (1+a\Delta t-b\Delta t\varphi_n)\varphi_n[/tex]), coefficient of grade 2 and 3 but, i don't know that more make
 

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  • #4
understand me? :(
 
  • #5
This equation is simple enough that it can be solved by separating the variables and the integrals are expressible in terms of elementary functions.
 
  • #6
How,... please, no solve all problem only the principe, because i have use a recorrencia formule...and least square method
 
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  • #7
help me please
 
  • #8
Ok, first of all, if you scale your independent variable:

[tex]
t = \tau \, t' \Rightarrow \frac{d}{dt} = \frac{1}{\tau} \, \frac{d}{dt'}
[/tex]

and you shift and scale your dependent variable:

[tex]
\varphi = \varphi_{0} + K \, y \Rightarrow d\varphi = K \, dy, \ y = y(t')
[/tex]

then your equation reduces to:

[tex]
\frac{K}{\tau} \, y' = (\varphi_{0} + K \, y) \, (a - b \, \varphi_{0} - b \, K \, y)
[/tex]

You impose the conditions:

[tex]
\left\{\begin{array}{rcl}
\varphi_{0} & = & K \\

a - b \, \varphi_{0} & = & b \, K \\

\frac{K}{\tau} & = & b \, K^{2}
\end{array}
\right.
[/tex]

that you need to solve for the arbitrary parameters you introduced [itex]\varphi_{0}, K, \tau[/itex]. The conditions were chosen such that your differential equation takes a simple form:

[tex]
\frac{d y}{d t'} = 1 - y^{2}
[/tex]

This ODE can be solved by the method of separation of variables:

[tex]
\frac{d y}{1 - y^{2}} = d t'
[/tex]

[tex]
\int{\frac{d y}{1 - y^{2}}} = t' + C_{1}
[/tex]

where [itex]C_{1}[/itex] is an arbitrary integration constant that needs to be determined from the initial conditions of the problem (of course, translated in terms of [itex](t' , y(t'))[/itex] instead of [itex](t, \varphi(t))[/itex]). The integral on the rhs can be evaluated by expanding the rational function in partial fractions and you should try and do it on your own.
 
  • #9
thanks!...but least square method and table atach that i put, i have that use
 
  • #10
yeah, i know, but you have to do your own work. Also, your English is incomprehensible.
 
  • #11
I know that my english is ugly sorry!, but i want solve this problem with a table and recorrence formula, not on way analytic
 
  • #12
then try and solve it and post your attempt.
 
  • #13
if I had no recurrence formula, I can solve and find [tex]\varphi_n[/tex] without a y b parameters with least square method, but the recurrence formula from differential equation is I not know how to use it together for the polynomial approximation by least square method of degree 2 and 3 as stated in the exercise
 

What is the "Question Least Square" method?

The Question Least Square method is a statistical technique used to find the best fit line to a set of data points. It minimizes the sum of the squared distances between the data points and the line, allowing for the relationship between variables to be quantified.

When would you use the "Question Least Square" method?

The Question Least Square method is commonly used in scientific research to analyze and understand the relationship between two or more variables. It is also frequently used in data analysis and modeling to make predictions and identify trends.

What are the limitations of the "Question Least Square" method?

While the Question Least Square method is a powerful tool, it does have some limitations. It assumes that the relationship between variables is linear, and it may not be suitable for data sets with outliers or extreme values. Additionally, it may not be appropriate for data sets with non-normal distributions.

How do you interpret the results of a "Question Least Square" analysis?

The results of a Question Least Square analysis are typically presented in the form of a regression equation, which represents the best fit line for the data. The slope of the line indicates the strength and direction of the relationship between the variables, and the intercept represents the value of the dependent variable when the independent variable is equal to zero.

Are there any alternatives to the "Question Least Square" method?

Yes, there are several alternative methods for analyzing the relationship between variables, including non-parametric methods, Bayesian regression, and machine learning techniques. These methods may be more appropriate for certain types of data or research questions.

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