Approaching probabilistic laws

Abstract In the general problem of verisimilitude, we try to define distance a statement from target, which is an informative truth about some domain investigation. For example, target can be state description, structure or constituent first-order language (Sect. 1). legisimilitude, deterministic universal law, expressed by nomic quantitative function involving operators physical necessity and possibility 2). The special case where probabilistic law 3), has been discussed Roger Rosenkrantz ( Synthese , 1980) Ilkka Niiniluoto Truthlikeness 1987, Ch. 11.5). Their basic proposal measure between two laws Kullback–Leibler notion divergence, semimetric on space probability measures. This idea applied coexistence succession, examples may involve discrete continuous spaces 3). this paper, these earlier studies are elaborated in four directions 4). First, even though limiting cases laws, target-sensitivity truthlikeness measures implies that legisimilitude not easily reducible case. Secondly, Jensen-Shannon divergence mixed entail laws. Thirdly, new class distributions proposed, so their horizontal differences taken into account addition vertical ones 5). Fourthly, solution given for epistemic estimating degrees basis empirical evidence 6).