Curve fitting is the process of constructing a curve or mathematical function, that has the best fit to a series of data points. Fitted curves can be used as an aid for data visualization, to conclude values of a function where no data are available, and to summarize the relationships among two or more variables.
Equation for Cauchy Curve is, $$ Y=\frac { I }{ \left[ 1+{ \left( \frac { x-a }{ \gamma } \right) }^{ 2 } \right] } $$ Where \(I\) is intensity,
\(a\) is Position,
\(\gamma\) is Scale parameter

Curve fitting is the process of constructing a curve or mathematical function, that has the best fit to a series of data points. Fitted curves can be used as an aid for data visualization, to conclude values of a function where no data are available, and to summarize the relationships among two or more variables.
Equation for Cauchy Curve is, $$ Y=\frac { I }{ \left[ 1+{ \left( \frac { x-a }{ \gamma } \right) }^{ 2 } \right] } $$ Where \(I\) is intensity,
\(a\) is Position,
\(\gamma\) is Scale parameter

Curve fitting is the process of constructing a curve or mathematical function, that has the best fit to a series of data points. Fitted curves can be used as an aid for data visualization, to conclude values of a function where no data are available, and to summarize the relationships among two or more variables.
Equation for Gaussian Curve is, $$ Y = A.{ e }^{ -\left( \frac { { \left( x-B \right) }^{ 2 } }{ 2{ C }^{ 2 } } \right) } $$ Where \(A\) is Height,
\(B\) is Position and
\(C\) is FWHM.

Curve fitting is the process of constructing a curve or mathematical function, that has the best fit to a series of data points. Fitted curves can be used as an aid for data visualization, to conclude values of a function where no data are available, and to summarize the relationships among two or more variables.
Equation for Gaussian Curve is, $$ Y = A.{ e }^{ -\left( \frac { { \left( x-B \right) }^{ 2 } }{ 2{ C }^{ 2 } } \right) } $$ Where \(A\) is Height,
\(B\) is Position and
\(C\) is FWHM.

Curve fitting is the process of constructing a curve or mathematical function, that has the best fit to a series of data points. Fitted curves can be used as an aid for data visualization, to conclude values of a function where no data are available, and to summarize the relationships among two or more variables.
Equation for Exponential Decay Curve is, $$ Y = \frac { 1 }{ B } .{ e }^{ \left( \frac { { A-x } }{ B } \right) } $$Where \(A\) is Position,
\(B\) is Scale parameter

Curve fitting is the process of constructing a curve or mathematical function, that has the best fit to a series of data points. Fitted curves can be used as an aid for data visualization, to conclude values of a function where no data are available, and to summarize the relationships among two or more variables.
Equation for Exponential Decay Curve is, $$ Y = \frac { 1 }{ B } .{ e }^{ \left( \frac { { A-x } }{ B } \right) } $$Where \(A\) is Position,
\(B\) is Scale parameter

Curve fitting is the process of constructing a curve or mathematical function, that has the best fit to a series of data points. Fitted curves can be used as an aid for data visualization, to conclude values of a function where no data are available, and to summarize the relationships among two or more variables. An equation for Straight Line is, Y = MX + C Where M is slope and C is intercept

Curve fitting is the process of constructing a curve or mathematical function, that has the best fit to a series of data points. Fitted curves can be used as an aid for data visualization, to conclude values of a function where no data are available, and to summarize the relationships among two or more variables. An equation for Straight Line is, Y = MX + C Where M is slope and C is intercept