Fixed effects modelIn statistics, a fixed effects model is a statistical model in which the model parameters are fixed or non-random quantities. This is in contrast to random effects models and mixed models in which all or some of the model parameters are random variables. In many applications including econometrics and biostatistics a fixed effects model refers to a regression model in which the group means are fixed (non-random) as opposed to a random effects model in which the group means are a random sample from a population.
Image editingImage editing encompasses the processes of altering s, whether they are digital photographs, traditional photo-chemical photographs, or illustrations. Traditional analog image editing is known as photo retouching, using tools such as an airbrush to modify photographs or editing illustrations with any traditional art medium. Graphic software programs, which can be broadly grouped into vector graphics editors, raster graphics editors, and 3D modelers, are the primary tools with which a user may manipulate, enhance, and transform images.
File attributeFile attributes are a type of meta-data that describe and may modify how and/or in a behave. Typical file attributes may, for example, indicate or specify whether a file is visible, modifiable, compressed, or encrypted. The availability of most file attributes depends on support by the underlying filesystem (such as , NTFS, ext4) where attribute data must be stored along with other control structures. Each attribute can have one of two states: set and cleared. Attributes are considered distinct from other metadata, such as dates and times, s or .
Extended file attributesExtended file attributes are features that enable users to associate s with metadata not interpreted by the filesystem, whereas regular attributes have a purpose strictly defined by the filesystem (such as or records of creation and modification times). Unlike , which can usually be as large as the maximum file size, extended attributes are usually limited in size to a value significantly smaller than the maximum file size.
Random effects modelIn statistics, a random effects model, also called a variance components model, is a statistical model where the model parameters are random variables. It is a kind of hierarchical linear model, which assumes that the data being analysed are drawn from a hierarchy of different populations whose differences relate to that hierarchy. A random effects model is a special case of a mixed model.