Search Results

To make the prediction interval for a particular forecast point , one needs to efficiently separate the data into signal and noise thus providing the "smallest model error variance" . Now the model mi …

You could simply adjust the limits by the difference between the two values. More generally one could include a predictor variable reflecting the user's specified probability of a particular event hap …

You have taken count data ( i.e.the number of failures in the first interval , the second interval , the nth interval ) and added them to create a cumulative series which is autocorrelated as a result …

In order to compute the variance of a sum of forecasts you need to incorporate the covariance between these forecasts. Thus compute the varriance and covariance of the observed series for as many lags …

There are simple methods to use but they are probably profoundly wrong as daily data presents a ton of opportunities . Simply striking daily averages is both simple and useless BUT I guess if there is …

I took your 29 days (oldest to newest) and found that there were 3 unusual days thus the following equation with Actual/Fit and Forecast here All models are wrong ... but some are useful .... . It …

ROUND TWO: You asked “how do I do this with the log-link function and quasi(Poisson) errors?”. I say put aside your priors suggesting a particular fixed model and use a data-driven empirical process t …

Generate a family of forecasts for each point in the future for all input series allowing for identified unusual values in the past of all input series to have an effect on the forecasts for these exo …

A possible alternative is to identify and form an efficient model generating a set of iid residuals. Generate a forecast using the model and then use the distribution of residuals as the basis of the …

You have a time series problem requiring a time series solution. The preferred method is an optimized weighted average of the past ... this method is called ARIMA or univariate Box-Jenkins. Concern ha …

you have to generate the psi weights which can be obtained by expressing the model as a pure long-lagged ma model https://rdrr.io/cran/tswge/man/psi.weights.wge.html . You also need the estimate of th …

Another way to pose your question is to ask "What is the probability of making a year-end number given that we have cumulative sales of xxx so far ?" . At a baseball game , after 3 boring innings I …

Whereas @javlacelle did a great job in developing the forecast variance for a particular case as he stated "The expressions of the variances vary with the order of the model", it is interesting to pur …