Sentence examples for incorrect variance from inspiring English sources

When the conditional variance is greater than the mean, an over-dispersed model may occur producing incorrect variance estimates that are biased downwards.

In general, bias can originate from preferential treatment, unrecognized pre-selection of validation animals, or inappropriate modeling of predictions (i.e. using incorrect variance components).

The potential for spatial correlation to result in incorrect variance estimates for exposure outcome measures in time series studies of health effects of air pollutants has been noted (Ramsay et al. 2003a, 2003b).

The consequences of an incorrect measurement error variance assessment can be assessed by running a series of models, each altering one fixed error variance to first "half" and then "double" the original fixed value.

This is a corrected model-based estimator that provides a consistent estimate of the covariance, making the statistical inference more robust to incorrect specification of the variance (e.g., if the variance exceeds the mean) and link function.

In such cases, one must conclude that the NJ tree is possibly incorrect due to the variance in the distance estimates.

In Table 2, the variance values were incorrect in the manuscript originally published online.

The other three approaches (Approaches 2a, 3a, and 3b) fail to incorporate sex effects, and give incorrect results when partitioning the variance components and calculating covariances between relatives.

Time series modeling accounts for autocorrelation, trend and seasonality which when present in data can cause ordinary regression techniques to present spurious variance estimates and incorrect inference.

We did not attempt to derive the expectations of estimated genetic parameters from the traditional direct indirect model (Equation 15) when the residual variance structure is incorrect (that is, different from that given in Equation 11).

When the mean estimates μ g, k are being treated as the intensity values x g, k,1, the mean and the incorrect summary statistic of the variance of this treatment condition are given as μ g = 1 K ∑ i = 1 K μ g, k, n o r m σ g 2 = 1 K ∑ i = 1 K (μ g, k − μ g ) 2 where n g = K Note that σ g 2 is equivalent to equation (3).