Man pages for chaudhary-amit/acblm
Two step estimation of three sided heterogeniety
| cluster.order | order cluster by increasing wage |
| dstats | provides statistics |
| em.control | Create a control structure for running EM algorithms |
| estimation.threeSided.model | Mixture model estimation of three sided model |
| get.largest.conset.fid | some work on trace formula Extracts the largest connected set... |
| get.largest.leaveoutset.fid | Extracts the largest leave-out connected set from data using... |
| get.sample.stats | computes simple statistics |
| grouping.append | Append result of a grouping to a data-set |
| grouping.classify | clusters firms based on their cross-sectional wage... |
| grouping.classify.once | clusters firms based on their cross-sectional wage... |
| grouping.computeobj | Compute the objective function of the clustering |
| grouping.getMeasures | Extract the measurement matrix to be given to the... |
| grouping.getMeasures.em | Get the three sided measures for inputs in clustering |
| grouping.infos | extract information |
| grouping.makefiner | Gives their won cluster to firm with many movers |
| jdata.prepare | Prepare the data for BLM from an employer-employee matched... |
| kmeansW.repeat | internal function that runs Kmean with multiple starting... |
| lin.proja | Generate a linear projection decomposition for the model with... |
| lin.projax | Computes the linear projection using X |
| lin.projx | Computes the linear projection using X |
| lognormpdf | functions for em |
| logRowSumExp | logsumexp function by Row |
| logsumexp | logsumexp function |
| m2.firmfe.pen | Ridge AKM |
| m2.get.pk_unc | Returns the uconditional type probability in the crossection |
| m2.mixt.estimate.all | Estimates the static mixture model on 2 periods |
| m2.mixt.meaneffect | Compute mean effects |
| m2.mixt.movers | Estimates the static model parameters for movers |
| m2.mixt.new | create a random model for EM with three sided endogenous... |
| m2.mixt.pplot | plots the proportions of a model |
| m2.mixt.simulate.movers | Using the model, simulates a dataset of movers |
| m2.mixt.simulate.sim | Simulates data (movers and stayers) and attached firms ids.... |
| m2.mixt.simulate.sim.clust | Simulates data (movers and stayers) |
| m2.mixt.simulate.stayers | Using the model, simulates a dataset of stayers. |
| m2.mixt.simulate.stayers.withx | Using the model, simulates a dataset of stayers. |
| m2.mixt.stayers | use the marginal distributions to extract type distributions... |
| m2.mixt.transform.data | Data tranformation ( 3d array to 2d array) |
| m2.mixt.transform.model | Model transformation for solver (3d array object to 2d array... |
| m2.mixt.vdec | Computes the variance decomposition by simulation |
| m2.mixt.wplot | plots the wages of a model |
| m2.movers.checkfit | check the fit in the movers/stayers using imputed data |
| m2.stayers.checkfit | check the fit in the movers/stayers using imputed data |
| m2.trace.estimate | gets the connected set, then |
| m2.trace.new | create a model for testing trace estimation |
| m2.trace.simulate | simulates for trace estimation |
| m2.trace.simulate.old | simulates for trace estimation |
| mcast | creates a matrix and fill it using a data.table in contrast... |
| model.connectiveness | Computes graph connectedness among the movers within each... |
| ModelInitializer | Prepare the finction for test run intialize the model... |
| plot.trquant | plots the conditional quantile distribution for each... |
| plot.vaeffect | we want to look at the effect of movers on value added. |
| plot.wage | plot the mean wage at origin conditional on where it is... |
| sample.stats | compute some stats on data |
| sColSums | Sparse colSums |
| set.solver.controls | Set the solver controls |
| Simulate.data.threeSided | Simulate the data consiting of three sided heterogeniety |
| spread | this is a utility function to generate multidimensional... |
| sRowSums | Sparse rowSums |
| threeSided.Clustering | Clustering (Step 1 of the estimation: Seep paper for details) |
| threeSided.means.plot | Estimated means plot |
| threeSided.proportion.plot | Proportion plot |
| vcast | creates a vector and fill it using a data.table in contrast... |
| wt.cov | Weighted covariance |
