The naive prognosis is probably the simplest of all prognoses, since it updates the current value or trend with elementary calculation methods for the future.

With respect to the technical literature between two types of the naive prognosis one differentiates:

• Type 1 (NO CHANGE prognosis): The current value is used as prognosis value.
• Type 2 (Same CHANGE prognosis): The last trend is used for the prognosis, i.e. the difference from last and next to last value is used for the computation of the prognosticated value.

The following formulas result thus for the naive prognosis:

\ mathsf {f_ {T-1}} = \ mathit {the last but one value} \ mathsf {f_ {t}} = \ mathit {current value}

• Type 1: \ mathsf {f_ {t+1}} = \ mathsf {f_ {t}}
• Type 2: \ mathsf {f_ {t+1}} = \ mathsf {f_ {t} + ({f_ {t}} - {f_ {T-1}})}

If the naive prognosis is used above all for it around the quality another, to judge prognosis computation. In addition the middle error of the prognosis which can be judged and the middle error of the naive prognosis are computed and from this the quotient is formed. If this characteristic value is smaller than 1, then the examined prognosis computation is better than the naive prognosis. That means that the additional expenditure, which is necessary for the prognosis was worthwhile itself.

A such evaluation is however only possible after actual occurring of the event, since for the computation the actual value is needed.

• Example of a naive prognosis: in a tourism municipality

Articles in category "Naive prognosis"

We found here 3 articles.

Related Websites

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  Abstract, Relationship of neuromotor disturbances to psychosis symptoms in first-episode neuroleptic-naive schizophrenia patients. Schizophr Res. ...


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  Preliminary evidence of striatal D2 receptor density as a possible biological marker of prognosis in naive schizophrenic patients. Perez V, Catafau AM, ...


• Prognosis of HIV-1-infected patients starting highly active ...
  BACKGROUND: Insufficient data are available from single cohort studies to allow estimation of the prognosis of HIV-1 infected, treatment-naive patients who ...


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  Objective: To apply naive Bayesian algorithm in prognosis prediction of primary liver cancer and to ...