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Without the zero mean qualifier it is not noise
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Taylor
Taylor
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An ARIMA(0,0,0) model with zero mean is white noise, so it means that the errors are uncorrelated across time.

This doesn't imply anything about the size of the errors, so no in general it is not an indication of good or bad fit.

In your case, you'll note that your $\sigma^2$ is 0.007612 and that ME is -6.321953e-17. These are very very small numbers, so yes, the model "fits" well.

However, the reason why they are very small is because you are fitting 15 parameters (14 coefficients + 1 error variance) to only 18 points.

You are likely overfitting the data to an extreme degree, and you will likely not be able to forecast out of sample very well.

An ARIMA(0,0,0) model is white noise, so it means that the errors are uncorrelated across time.

This doesn't imply anything about the size of the errors, so no in general it is not an indication of good or bad fit.

In your case, you'll note that your $\sigma^2$ is 0.007612 and that ME is -6.321953e-17. These are very very small numbers, so yes, the model "fits" well.

However, the reason why they are very small is because you are fitting 15 parameters (14 coefficients + 1 error variance) to only 18 points.

You are likely overfitting the data to an extreme degree, and you will likely not be able to forecast out of sample very well.

An ARIMA(0,0,0) model with zero mean is white noise, so it means that the errors are uncorrelated across time.

This doesn't imply anything about the size of the errors, so no in general it is not an indication of good or bad fit.

In your case, you'll note that your $\sigma^2$ is 0.007612 and that ME is -6.321953e-17. These are very very small numbers, so yes, the model "fits" well.

However, the reason why they are very small is because you are fitting 15 parameters (14 coefficients + 1 error variance) to only 18 points.

You are likely overfitting the data to an extreme degree, and you will likely not be able to forecast out of sample very well.

Formatting and including Math-jax equation
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edit approved Sep 26, 2016 at 11:43
Ferdi
edit approved Sep 26, 2016 at 11:43
Ferdi
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An ARIMA(0,0,0)ARIMA(0,0,0) model is white noise, so it means that the errors are uncorrelated across time. 

This doesn't imply anything about the size of the errors, so no in general it is not an indication of good or bad fit.

In your case, you'll note that your sigma^2 is 0.007612$\sigma^2$ is 0.007612 and that ME is -6.321953e-17.-6.321953e-17. These are very very small numbers, so yes, the model "fits" well. 

However, the reason why they are very small is because you are fitting 15 parameters (14 coefficients + 1 error variance)15 parameters (14 coefficients + 1 error variance) to only 18 points18 points. 

You are likely overfitting the data to an extreme degree, and you will likely not be able to forecast out of sample very well.

An ARIMA(0,0,0) model is white noise, so it means that the errors are uncorrelated across time. This doesn't imply anything about the size of the errors, so no in general it is not an indication of good or bad fit.

In your case, you'll note that your sigma^2 is 0.007612 and that ME is -6.321953e-17. These are very very small numbers, so yes, the model "fits" well. However, the reason why they are very small is because you are fitting 15 parameters (14 coefficients + 1 error variance) to only 18 points. You are likely overfitting the data to an extreme degree, and you will likely not be able to forecast out of sample very well.

An ARIMA(0,0,0) model is white noise, so it means that the errors are uncorrelated across time. 

This doesn't imply anything about the size of the errors, so no in general it is not an indication of good or bad fit.

In your case, you'll note that your $\sigma^2$ is 0.007612 and that ME is -6.321953e-17. These are very very small numbers, so yes, the model "fits" well. 

However, the reason why they are very small is because you are fitting 15 parameters (14 coefficients + 1 error variance) to only 18 points. 

You are likely overfitting the data to an extreme degree, and you will likely not be able to forecast out of sample very well.

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Chris Haug
Chris Haug
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An ARIMA(0,0,0) model is white noise, so it means that the errors are uncorrelated across time. This doesn't imply anything about the size of the errors, so no in general it is not an indication of good or bad fit.

In your case, you'll note that your sigma^2 is 0.007612 and that ME is -6.321953e-17. These are very very small numbers, so yes, the model "fits" well. However, the reason why they are very small is because you are fitting 15 parameters (14 coefficients + 1 error variance) to only 18 points. You are likely overfitting the data to an extreme degree, and you will likely not be able to forecast out of sample very well.