I am trying figure out what is the difference between Brown's linear model for double exponential smoothing and Holt's model. So the differences can be implemented into a Holt model using if statements. Aside from having alpha for both the trend and smoothing component.

I am having a problem where the forecasting occurs when the level equation is added to the trend equation to forecast:

IBM SPSS also a difference when forecasting k steps ahead where ((k-1)+(alpha^-1))

But in other books and articles it shows that for the forecast equation the level and trend is converted.

Are the SPSS equation and the other one the same? (I am asking because it is easier to implement one over the other)

Also what is recommended for the initial points? And did I miss any differences?

I am trying figure out what is the difference between Brown's linear model for double exponential smoothing and Holt's model. So the differences can be implemented into a Holt model using if statements. Aside from having alpha for both the trend and smoothing component.

I am having a problem where the forecasting occurs when the level equation is added to the trend equation to forecast:

IBM SPSS show that when forecasting k steps ahead ((k-1)+(alpha^-1)) is used.

But in other books and articles it shows that for the forecast equation for the level and trend is changed to 'at' and 'bt' before being added together.

Are the SPSS equation and the other one the same? (I am asking because it is easier to implement one over the other)

Also what is recommended for the initial points? And did I miss any differences?

I am trying figure out what is the difference between Brown's linear model for double exponential smoothing and Holt's model. Aside from having alpha for both the trend and smoothing component.

IBM SPSS also a difference when forecasting k steps ahead where ((k-1)+(alpha^-1))

But in other books and articles it shows that for the forecast equation the level and trend is converted.

Are the SPSS equation and the other one the same? (I am asking because it is easier to implement one over the other)

I am trying figure out what is the difference between Brown's linear model for double exponential smoothing and Holt's model. So the differences can be implemented into a Holt model using if statements. Aside from having alpha for both the trend and smoothing component.

I am having a problem where the forecasting occurs when the level equation is added to the trend equation to forecast:

IBM SPSS also a difference when forecasting k steps ahead where ((k-1)+(alpha^-1))

But in other books and articles it shows that for the forecast equation the level and trend is converted.

Are the SPSS equation and the other one the same? (I am asking because it is easier to implement one over the other)

Also what is recommended for the initial points? And did I miss any differences?

I am trying figure out what is the difference between Brown's linear model for DES and Holt's model. Aside from having alpha for both the trend and smoothing component?

IBM SPSS also a difference when forecasting k steps ahead where ((k-1)+(alpha^-1))

But in other books and articles it shows that for the forecast equation the level and trend is converted.

Are the SPSS equation and the other one the same? (I am asking because it is easier to implement one over the other)

I am trying figure out what is the difference between Brown's linear model for double exponential smoothing and Holt's model. Aside from having alpha for both the trend and smoothing component.

IBM SPSS also a difference when forecasting k steps ahead where ((k-1)+(alpha^-1))

But in other books and articles it shows that for the forecast equation the level and trend is converted.

Are the SPSS equation and the other one the same? (I am asking because it is easier to implement one over the other)