Selecting Forecasting Methods

I examined six ways of selecting forecasting methods: Convenience, “what’s easy,” is inexpensive, but risky. Market popularity, “what others do,” sounds appealing but is unlikely to be of value because popularity and success may not be related and because it overlooks some methods. Structured judgment, “what experts advise,” which is to rate methods against prespecified criteria, is promising. Statistical criteria, “what should work,” are widely used and valuable, but risky if applied narrowly. Relative track records, “what has worked in this situation,” are expensive because they depend on conducting evaluation studies. Guidelines from prior research, “what works in this type of situation,” relies on published research and offers a low-cost, effective approach to selection. Using a systematic review of prior research, I developed a flow chart to guide forecasters in selecting among ten forecasting methods. Some key findings: Given enough data, quantitative methods are more accurate than judgmental methods. When large changes are expected, causal methods are more accurate than naive methods. Simple methods are preferable to complex methods; they are easier to understand, less expensive, and seldom less accurate. To select a judgmental method, determine whether there are large changes, frequent forecasts, conflicts among decision makers, and policy considerations. To select a quantitative method, consider the level of knowledge about relationships, the amount of change involved, the type of data, the need for policy analysis, and the extent of domain knowledge. When selection is difficult, combine forecasts from different methods

Uncoupled activation and cyclization in catmint reductive terpenoid biosynthesis

Terpene synthases typically form complex molecular scaffolds by concerted activation and cyclization of linear starting materials in a single enzyme active site. Here we show that iridoid synthase, an atypical reductive terpene synthase, catalyzes the activation of its substrate 8-oxogeranial into a reactive enol intermediate, but does not catalyze the subsequent cyclization into nepetalactol. This discovery led us to identify a class of nepetalactol-related short-chain dehydrogenase enzymes (NEPS) from catmint (Nepeta mussinii) that capture this reactive intermediate and catalyze the stereoselective cyclisation into distinct nepetalactol stereoisomers. Subsequent oxidation of nepetalactols by NEPS1 provides nepetalactones, metabolites that are well known for both insect-repellent activity and euphoric effect in cats. Structural characterization of the NEPS3 cyclase reveals that it binds to NAD+ yet does not utilize it chemically for a non-oxidoreductive formal [4 + 2] cyclization. These discoveries will complement metabolic reconstructions of iridoid and monoterpene indole alkaloid biosynthesis

Comparison of a new calculation of energy-energy correlations with e+ e- ---> hadrons data at the Z0 resonance

We have compared a new QCD calculation by Clay and Ellis of energy-energy correlations (EEC's) and their asymmetry (AEEC's) in e(+)e(-) annihilation into hadrons with data collected by the SLD experiment at SLAG. From fits of the new calculation, complete at O(alpha(s)(2)), we obtained alpha(s)(M(Z)(2)) = 0.1184 +/- 0.0031 (expt) +/- 0.0129 (theory) (EEC) and alpha(s)(M(Z)(2)) = 0.1120 +/- 0.0034 (expt) +/- 0.0036 (theory) (AEEC). The EEC result is significantly lower than that obtained from comparable fits using the O(alpha(s)(2)) calculation of Kunszt and Nason