In order to analyze the responses of all 30 Player 2s to the full range of 9 possible moves by Player 1, we use a linear estimator (OLS) with robust standard errors.
Data comparisons between genotype groups were made using a linear model and Huber–White sandwich estimator/robust standard errors, accounting for layers of data clustering due to assay batches and from shared genetic/environmental factors in related twins.
In this paper three estimator implementation methods are used and compared: a linear estimator, an estimator based on a feedforward neural network with continuous values and an estimator based on an ANFIS.
Prevalence estimates are reported with their 95% confidence intervals (CI); standard errors were calculated using a linearized variance estimator based on a first-order Taylor series linear approximation.
Since the transmitters are required to be simple in design, we assume that a linear estimator is used at each transmitter for estimating the channel coefficient, such as a linear MMSE estimator.
Thus, assuming we use a linear model, a general estimator of E is given as widehat{Eleft {tau}^right)}={displaystyle {sum}_{iin s}frac{{boldsymbol{X}}_{boldsymbol{i}} widehat{boldsymbol{beta}}}{pi_i}={boldsymbol{pi}}^{boldsymbol{prime}}boldsymbol{X}widehat{boldsymbol{beta}}} (8).
where is a linear estimator of.
Since the transmitters are required to be simple in design, we assume that each transmitter obtains its CSI by estimating the channel coefficient using some linear estimator, such as a linear Minimum Mean Square Error(MMSE) estimator.
The influence of lack of legal status, age and gender was analyzed using a generalized linear model with robust estimators.
A generalized linear mixed-effects regression model (Poisson distribution) was fit to the counts of communities per matrilineal groom network using a robust estimator (aka Huber variance) of the covariance matrix [52].
