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A consumption based proxy variable is assumed to represent economic standard of households.
In ARIMA models, the future value of a variable is assumed to be a linear function of the past values and error terms.
The damage variable is assumed to be related to the increase in porosity resulting from the loss of mass from the formation rock matrix.
This variable is assumed to affect the probability of participation in rice output markets, but is assumed not to influence the farmers' welfare.
The damage variable is assumed to be related to the increase in porosity resulting from the loss of mass from formation rock matrix.
If the missing input variable is assumed to have a finite number of values the method proposed here may be compared to mixture of experts and mixture density networks except that the proposed method is more direct solution.
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Individual designs comprising up to k+1 distinct and equally spaced values of the explanatory variable are assumed to be available.
We assessed the relationship between ant density and behavior using a generalized linear mixed model with the lmer function from lme4 package in R. Because behavior was recorded as counts, each independent variable was assumed to be distributed as a Poisson random variable.
This variable was assumed to be time-invariant.
Missing information within each variable was assumed to be random, and 10 imputations were included in the model.
The correlation between two observations of any neuropsychological variable was assumed to follow an autoregressive correlation model of order 1.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com