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A statement of the chance that an unknown quantity in reality has a particular value based on the readiness with which it would account for a given set of data; in this way the merits of various competing interpretations may be compared.
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Patient discussion about likelihood

Q. What is the likelihood of my depression returning? I have a history of severe depression. My mom is very against medication and counseling, and reluctantly allowed me to go on the lowest dosage of zoloft. It helped, but now she wants me to go off of it and stop going to my doctor. My fear is that my depression will return. What are the chances of my depression returning, and how can I handle it if and when it does?

A. hi kelly17 i agree with eleanor55, i donot have bi-polar-but it seems to me that the problem isnt YOU/it your mother-Im going to be real here-if your mother knows that the meds help why is she stopping them--I think the stigma of the disease is her problem,like the other members said, and if she is doing this to you for that reason/BAD ON HER---at 17 i think you are under age--I dont want to start a family feud but i think this is child abuse--talk to soom one at school teacher/ect----stay strong things get better with time you have a lot of friends her USE THEM---mrfot56

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References in periodicals archive ?
The likelihood function was defined from the distance function and each number of data sets (T) from 1 to 10 was put into the likelihood function.
Given the data measurement error [[xi].sub.i] ~ Normal(0, [[sigma].sup.2]), the likelihood function for an individual data point at the time point t is
In this study we use the procedure in [15] where the maximum likelihood estimator of p is obtained by directly maximizing the profile likelihood function. For any given value of p we find the maximum likelihood estimate of [beta], [THETA] and compute the log-likelihood function.
To obtain estimator [[??].sub.[OMEGA]] ([u.sub.i], [v.sub.i]) we form likelihood function under population parameter space L([OMEGA]).
Since the number of samples T was known, the partial derivative of the logarithmic likelihood function for the connection weight [W.sub.ij], the offset [a.sub.i] of the visible layer element, and the offset [b.sub.j] of the hidden layer unit could be expressed by P(h|[V.sup.(t)], [theta]) and P(v, h | [theta]).
Conversely, given ([h.sup.+.sub.u], [h.sup.-.sub.u]) and [([h.sup.+.sub.u], [h.sup.-.sub.u]) : i [member of] Ij, the same formula can be interpreted as a function of [theta], called the individual likelihood function for one trip of a passenger.
The global likelihood functions were constructed using 16 out of the 37 original datasets, four from each fault case, using datasets which were independent from the datasets used when constructing the local likelihood functions.
In this paper, the time delay likelihood function under the condition of multipath is deduced by using channel frequency response.
Based on this received signal model, we derive an accurate closed-form formula of the likelihood function and propose a modified LLR calculation algorithm.
Considering that the measurements are independent of each other, the likelihood function of the observed values [y.sub.1], [y.sub.2], ..., [y.sub.N] is
observed data at times ([t.sub.1], [t.sub.2], ..., [t.sub.n]) from the model defined by (1) and (4), and then the likelihood function is given by
The usual practice for statistical inference is to use the natural logarithm of the likelihood function, namely, the log-likelihood function, which is given by