1. A method of computer-estimating a target parameter in time-dependent data using: (A) a first function that relates at least one varying output parameter to at least one varying input parameter known only with some uncertainty, the function's varying parameters including a set of one or more measured variables having associated measurement error, and at least one of the varying parameters being a target parameter for which an estimate is desired; and (B) a second function that relates at least one varying output parameter to at least one varying input parameter known only with some uncertainty, the second function's varying parameters including at least one measured variable having associated measurement error, and at least one of the varying parameters being a second target parameter for which an estimate is also desired, the method comprising, with a computer, automatically: (a) performing a first pass, with respect to one of the first or second functions, comprising: (i) receiving a first measurement of one of the measured variables of the function, measured at a first time; (ii) receiving a first probability distribution of the varying input parameters of the function; (iii) receiving first bounds for the output parameter of the function based on known real-world constraints on possible values of the output parameter; (iv) wherein measurement error associated with the measured variable influences the first probability distribution or first bounds of the measured variable; (v) drawing a plurality of values of the varying input parameters, which draws are randomized using the first probability distribution of the varying input parameters, and applying the function to each drawn value to determine an associated value of the output parameter; (vi) for the draws, comparing the determined value of the output parameter to the bounds; and (vii) applying a formula to the set of values of the target variable of the function associated with drawn values that result in values of the output parameter that are within the first bounds, to calculate information about the target parameter of the function; (b) performing a second pass, with respect to the other one of the first or second functions comprising: (i) receiving a second measurement of one of the measured variables of the function, measured at a second time that is different than the first time; (ii) receiving a second probability distribution of the varying input parameters of the function; (iii) receiving second bounds for the output parameter of the function based on known real-world constraints on possible values of the output parameter; (iv) wherein measurement error associated with the measured variable influences the second probability distribution or second bounds of the measured variable; (v) drawing a plurality of values of the varying input parameters, which draws are randomized using the second probability distribution of the varying input parameters, and applying the function to each drawn value to determine an associated value of the output parameter; (vi) for the draws, comparing the determined value of the output parameter to the second bounds; (vii) applying a formula to the set of values of the target variable of the function associated with drawn values that result in values of the output parameter that are within the second bounds, to calculate information about the target parameter of the function; and (viii) storing or displaying the calculated information about the target parameter; (c) wherein the target parameter of the function with respect to which the first pass is performed is a parameter common to the first function and the second function; and (d) wherein information calculated about that common parameter is used on the second pass either: (i) to define at least one bound on the second probability distribution, or (ii) to define at least one second bound.