@@ -166,7 +166,6 @@ (:documentation "empirical characteristics for a continuous statistical variable")) - (defmethod print-object ((object statistical-variable) stream) "Need to work through how to print various objects. Statvars don't necessarily have data yet!" @@ -178,7 +177,54 @@ necessarily have data yet!" necessarily have data yet! Here, we should print out the stat-var information, (pass to superclass) and then print out factor levels if short enough (exact class). Useful to review methods-mixing for -this." +this, first bit should be indentical to stat-var." (print-unreadable-object (object stream :type t) (format stream "nobs=~d" (nobs object)) - (format stream "levels=~A" (factor-levels object)))) \ No newline at end of file + (format stream "levels=~A" (factor-levels object)))) + +;;; Observations +;;; + +(defclass statistical-observation () + ((measurement-types :initform nil + :initarg measurement-types + :accessor measurement-types + :type sequence + :documentation "sequence of types corresponding + to the classes of entries which have been measured/recorded to form + the observation.") + (record :initform nil + :initarg record + :accessor record + :type sequence + :documentation "the sequence of data which is a realization + of the corresponding measurement type")) + (:documentation "denotes a vector of measurements, not necesarily + simple (i.e. entries could be scalar, array, network) which can be + assumed to be independent or at least conditionally independent + given measurements external to the collected dataset. Failure of + this condition implies a single observation, not multiple + observations.")) + +;;; At this point, from a dataframe, which is just a simple holding +;;; structure, we should be able to extract variables and +;;; observations, which ought to be coherent, atomic, complex objects. +;;; (to create a wonderful contradiction: consider the time-series +;;; from the Dow Jones Industrial Average -- in this case, we need +;;; would have a dataset consisting of 1 observation and 1 variable -- +;;; which would be the singular time series (at whatever temporal +;;; resolution was desired). + +;;; For now, we need to have a means of extracting components of the +;;; dataframe into corresponding variables and observations as +;;; needed. We don't build up the dataframe directly from variables +;;; (yet -- this could change as we consider the workflow/API +;;; approach) but rather we tear-down the dataframe through +;;; consideration of variables and observations. + +;;; this naturally means that this is metadata on top of the +;;; dataframe, rather than building the dataframe on top of metadata. +;;; For pragmatic reasons, it isn't always clear that the dataframe +;;; MUST correspond to the particular instance of the practical +;;; statistical philosophy espoused in this system. But at some more +;;; mature point, it should be. src/data/data.lisp f4ca2a6ae52e1625938298f8ec762e88576b03cf AJ Rossini blindglobe@gmail.com http://github.com/blindglobe/common-lisp-stat/commit/b0b23576b937cf4d29146e6cb5ee11f078ddd6b9 b0b23576b937cf4d29146e6cb5ee11f078ddd6b9 2009-10-29T00:16:16-07:00 2009-10-29T00:16:16-07:00 getting dataframe philosophy right, finally! added initial data structure for observations, and comments/documentation for how it should all fit together. Signed-off-by: AJ Rossini <blindglobe@gmail.com> 45fbc1ea0c08d378bb756bbbcf11299beffa6769 AJ Rossini blindglobe@gmail.com